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לפני 2 שעות
חברה חסויה
Location: Merkaz
Job Type: Full Time and Hybrid work
We're hiring a Quality Lead to own that. Why this role is different: you won't run a traditional QA team that tests features at the end. You'll own the quality gates inside the Machine and in production, author the monitoring skills our pods rely on, and hold independent authority to fail the Machine's output. Quality is our north star, and this role sets the bar.
THE MISSION: Make reliability, performance, and user experience a property of the system - not of individual heroics. Build and lead a Quality function (~9 people) that keeps an AI-native delivery org fast and trustworthy, and give the business confidence that what the Machine ships is safe to ship.
WHAT YOU'LL DO:
Own quality gates in the Machine - prose-driven tests (generated from requirements, not the code), adversarial / agent-checks-agent review, static analysis and code-quality remediation (e.g. SonarCloud), and CI gates that run before anything reaches a human.
Own quality in production - release verification, production testing, and ownership of change-fail and deployment-rework rates.
Author monitoring guidelines & reusable observability skills that delivery pods and the Machine consume - so monitoring is built in, not bolted on.
Own the evals that score the Machine's output for behavioral consistency and reliability - treating evaluation as a first-class engineering discipline.
Act as an independent governance voice - with the authority to block or fail output that doesn't meet the bar, partnering closely with Architecture.
Partner with the Core Platform team on the quality of customer-issue fixes and existing functionality.
Lead, coach and grow the team - quality/gate engineers, an agent-evaluation engineer, production-monitoring (SRE) and QA-infrastructure engineers.
Set the quality metrics and report them - DORA + deployment-rework rate, escaped-defect rate, review-queue depth, eval pass rates.
Requirements:
7+ years in software quality / QA engineering, including leading a team, ideally owning quality for a SaaS product at scale.
Deep hands-on experience with test automation, CI/CD, and quality gates;
comfort with code-quality tooling (SonarQube/SonarCloud or similar).
Strong production monitoring / observability background (Datadog or
equivalent) and SRE-adjacent practices; monitoring-as-code a plus.
Fluency with engineering metrics - DORA, change-fail / rework rate, defect
escape - and using them to drive decisions.
Comfortable with AI-assisted / agentic development and evaluating LLM/agent
output (evals) - or a strong, demonstrated eagerness to go deep here.
A player-coach: credible hands-on and able to build and grow a team.
Able to hold an independent line and manage stakeholders across Engineering
and Product.
Professional English; based in (or able to work from) our Ukraine delivery center.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for an Engineering Team Lead, who will be responsible for the foundational infrastructure framework used by all our company engineering teams to build, deploy, and operate AI agents safely in production. We are building the "operating system" for AI at our company, covering agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. You will lead a high-impact team of 5 engineers to create the runtime and platform that defines the future of autonomous enterprise intelligence.
Youll Own:
Agentic Framework Architecture: Designing and building our companys internal agentic framework, leveraging and integrating industry-standard tools such as LangChain, LangSmith, ADK, and similar ecosystems.
Evaluation and Quality Systems: Building evaluation frameworks and workflows for AI agents, including offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
Team Leadership & Mentorship: Leading a squad of 3-4 senior engineers, fostering a culture of technical excellence, and managing end-to-end delivery in a fast-paced environment. You will spend approximately 50% of your time hands-on, architecting core systems and reviewing code, and 50% leading the team, mentoring engineers, and aligning with cross-functional stakeholders.
Observability, Monitoring, and Guardrails: Providing the organization with robust observability capabilities for AI agents, including tracing, logging, monitoring, cost tracking, and safety guardrails to ensure reliable and responsible usage.
Developer Enablement Platforms: Creating APIs, SDKs, and abstractions that enable product teams to easily build, test, and operate agents while adhering to platform standards.
Cross-Language Integrations: Designing integrations and tooling across Python and Java to enable seamless adoption of the AI framework within our companys broader backend ecosystem.
Youll Solve:
Agent Lifecycle and Orchestration Complexity: Managing agent execution, tool usage, memory, workflows, and failure modes in production-grade systems.
AI System Reliability at Scale: Ensuring agents remain observable, debuggable, and safe as usage scales across teams and products.
Evaluation and Drift Challenges: Detecting quality regressions, model behavior changes, and unintended agent behaviors through robust evaluation and monitoring systems.
Platform Adoption Friction: Balancing flexibility with guardrails so teams can innovate quickly without compromising reliability, security, or cost controls.
Youll Impact:
Company-Wide AI Enablement: Empowering every engineering team at our company to build agent-based solutions faster, with higher quality and confidence.
Foundational AI Infrastructure: Establishing the core frameworks, evaluations, and observability standards that all AI agents at our company will rely on.
AI Safety and Quality Bar: Raising the bar for how AI systems are evaluated, monitored, and governed across the company.
Requirements:
8+ years of backend engineering experience, with strong system design and platform-building expertise. Tech leadership or team leading experience is an advantage.
Strong analytical and problem-solving skills, with the ability to debug and resolve complex technical issues efficiently.
Hands-on experience with agentic systems and frameworks such as LangChain, LangSmith, ADK, or equivalent agent orchestration platforms.
Strong understanding of AI evaluation methodologies, including agent evaluations, prompt evaluation, regression testing, and quality monitoring.
High proficiency in Python for building production-grade AI frameworks and services.
Familiarity with Java and experience integrating backend platforms or tooling into Java-based systems.
Experience building observability, monitoring, or platform tooling for distributed systems.
Strong analytical skills and the ability to reason about complex, evolving AI-driven systems.
This position is open to all candidates.
 
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30/08/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Head of Forward Deployed Engineering to lead the team that turns our platform into live production systems inside the largest enterprises. You will own a team of 10+ FDEs (and growing), the delivery bar they are held to, and the outcomes they ship.
This is a player-coach role. You set the standard, build the system that enforces it, and stay close enough to the work to review a flow design and call out what's wrong.
What You'll Do
Own delivery outcomes. On-time go-lives, production stability and client satisfaction all land on your desk. You manage by data: delivery metrics, quality signals, escalation rates and client feedback.
Raise the bar. Run a clear performance system with a defined FDE bar, 30-60-90 ramps for new hires, and honest evaluations. Coach the people who can grow. Make the hard calls on those who can't.
Run the operating rhythm. Own the flow review forum, the deployment status cadence, and the on-site schedule across clients.
Grow the team. Own the hiring pipe, from sourcing through a practical interview loop to onboarding that gets new FDEs to independent delivery in 90 days.
Stay in the field. Show up at key clients, especially around go-lives. Your credibility comes from being in the room, not above it.
Requirements:
3+ years managing a technical delivery team such as solutions engineering, professional services or implementation (team of 5 to 15).
Technical depth. You can review a solution design, challenge an integration approach, and understand LLM-based systems well enough to hold a quality bar.
Proven bar-raising. You have inherited a team, defined what good looks like, measured against it, and acted on the results, including the uncomfortable parts.
Comfortable in front of enterprise stakeholders, from steering committees to go-live war rooms.
Clear thinking and clear writing. Hebrew fluency and strong English.
This position is open to all candidates.
 
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08/09/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior Data Engineer to build and scale the data foundation behind platform and products. You will own complex data end-to-end - from ingestion and transformation through modeling, quality, observability, and production delivery.
This is a hands-on senior IC role for a strong builder who can solve difficult data problems independently, set a high technical bar, and collaborate closely with engineering, DS, and product. You will turn large, fragmented datasets into reliable, reusable capabilities that power every product.
Responsibilities
Build and own scalable data pipelines- Design, implement, and operate robust pipelines for high-volume structured and unstructured data, with validation, monitoring, lineage, and recovery built in.
Scale the platform for growth- A key near-term initiative is re-architecting the system to support a significantly larger customer base. You will own performance and cost-efficiency across pipelines and services, keeping reliability and operating costs under control as the platform scales.
Build across the stack- This is not a pipelines-only role. You will also write backend services and some frontend, including the internal backoffice the team runs on. We hire builders, not narrow specialists.
Own the core data tables- Own schema design and evolution, data contracts, and the modeling standards the team follows - naming, shared dimensions, normalization, documentation. Be accountable when a table is wrong, late, or drifting.
Level up the teams data work- Pair with and advise software engineers and data scientists on Spark, SQL, and modeling, and help turn notebook-grade code into production-grade pipelines.
Partner cross-functionally- Translate product, client, compliance, and business requirements into clear technical designs and dependable production systems.
Requirements:
Spark at scale- You have tuned real Spark jobs for performance and cost - skew, shuffle, partitioning, memory, spill - run pipelines over TB-scale or billions of rows in production, and can reason about the physical execution plan, not just write DataFrame code.
5+ years of professional experience building and owning production systems.
Strong Python and SQL, with maintainable, tested production code.
Strong software engineering fundamentals across the stack. You can own backend services and pick up frontend when the work needs it - not a pipelines-only specialist.
AI-first way of working- You build with AI in your day-to-day development, using it to move faster and raise the quality of what you ship.
Deep experience designing and operating ETL/ELT pipelines, data models, and distributed data-processing systems.
Comfortable advising and pairing with other engineers and data scientists on data work.
Strong AWS experience: S3, Glue, EMR, Athena, and related compute and orchestration services.
Experience with modern data lakehouse or warehouse architectures. Apache Iceberg is a strong advantage.
Experience with workflow orchestration (Airflow or similar), CI/CD, Docker, Git, and infrastructure as code such as AWS CDK and CloudFormation.
Strong understanding of data quality, schema evolution, lineage, observability, privacy, security, and access controls. Experience with regulated or sensitive data, such as healthcare / PHI, is an advantage.
High comfort in a fast-moving environment with incomplete requirements, high ownership, and a strong sense of urgency.
This position is open to all candidates.
 
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Location: Bnei Brak
Job Type: Full Time
we are looking for a Senior AI Engineer - Exploration & Prototyping.
That is this role. You take an open question, run a focused spike, and come back with numbers and a recommendation. You read the source of the frameworks you evaluate rather than trusting their marketing. You build prototypes to settle arguments.
You do not own a subsystem and you do not ship to customers, which is exactly what protects the work: exploration inside a delivery team always loses to the sprint. You sit alongside the platform, research, and forward-deployed teams, you borrow their context freely, and your output is evidence they can act on.
You will be trusted with real influence early. The recommendations you write become the architecture other people build against, so the bar is not a working demo but a defensible conclusion, including the ones that say no.
What Youll Do:
Run technical spikes that close open decisions, covering agent orchestration frameworks, real-time transport, memory protocols, agent interoperability standards, LLM selection and routing, evaluation harnesses, and the production library and stack choices underneath all of it.
Build prototypes to de-risk, standing up something real quickly, proving or disproving the thing in question, and moving on without becoming attached to the code.
Read and evaluate unfamiliar codebases, going into the source of a candidate framework to find out whether it can actually support what we need rather than what its documentation implies.
Design the measurements that make a decision defensible, building the harness, running the comparison, and reporting latency, cost, and failure behavior honestly.
Own build-versus-adopt recommendations for platform infrastructure, frameworks, and libraries, including a clear statement of what it would cost to be wrong.
Write the recommendation down. Every spike ends in a short, decisive document another engineer can act on, with the evidence, the rejected options, and the reasoning behind the call
Hand off cleanly, transferring what you learned to the team that will own the capability in production, and staying available while they pick it up.
Track the landscape across agentic infrastructure, real-time frameworks, and adjacent AI tooling, and bring forward the things that genuinely change what we can build.
Requirements:
B.Sc. in Computer Science (or equivalent technical field), mandatory.
7+ years of industry experience in software, ML, or research engineering roles, with real ownership of production systems.
Genuine technical breadth. You have worked across backend services, runtime, and infrastructure, and you are comfortable close to ML systems without needing to own the models. You can hold several unfamiliar domains at once.
Strong Python skills, and the ability to get something real running quickly.
A track record of technical evaluations that led to decisions, where you compared real options, produced evidence, and the organization acted on the result.
Evidence over intuition. You have designed benchmarks or measuremet harnesses, and you can describe a time you were convinced something would work and the numbers said otherwise.
Experience with real-time, streaming, or latency-sensitive systems.
Hands-on experience with LLMs and agentic systems, including orchestration, tool calling, and how these systems behave and fail in production.
Comfortable working as an individual contributor without a team, self-directed, and able to finish. Exploration that never lands is the failure mode of this role.
Experience in a fast-moving SaaS company and in cloud environments (AWS, GCP, or Azure).
This position is open to all candidates.
 
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16/08/2026
חברה חסויה
Location: Herzliya
Job Type: Full Time and Hybrid work
we are looking for a QA Lead, Business Applications.
This position combines leadership with hands-on execution. You will define quality strategies for large cross-functional initiatives, including test scope, coverage, risk assessment, and release readiness criteria. You'll review developer test plans, execute end-to-end and exploratory testing, and oversee post-production validation across complex payment flows, pricing configurations, and service integrations.
Success in this role requires a deep understanding of end-to-end customer experiences, spanning backend services and customer-facing products. You will partner closely with Engineering and Product teams to ensure systems are designed with quality and testability in mind from the start.
As AI continues to transform software development, we are looking for someone who can leverage AI-powered tools to improve testing efficiency, accelerate defect analysis, optimize regression coverage, and enhance overall quality processes. You'll play a key role in shaping how modern quality practices evolve .
What you'll do:
Own the go/no-go recommendation for production releases by assessing testing progress, quality readiness, and overall risk.
Lead end-to-end quality strategy for large cross-team initiatives, from planning and design through production monitoring and validation.
Define test scope, coverage models, risk areas, rollout strategies, and quality KPIs for complex features and programs.
Validate complex business workflows, pricing configurations, customer entitlements, payment journeys, integrations, microservices, and event-driven systems through E2E, regression, exploratory, and API testing.
Use AI tools to accelerate test design, defect triage, regression planning, and coverage analysis while continuously improving team workflows.
Review and approve developer-authored test plans, ensuring sufficient coverage across positive, negative, edge-case, integration, and failure scenarios.
Partner with Engineering and Product teams early in the design process to identify quality risks and improve system testability.
Mentor developers and QA engineers on testing strategy, quality best practices, and automation analysis while helping standardize QA processes across teams.
Monitor production quality, own post-production validation activities, and manage QA-related technical debt.
דרישות:
5+ years of experience in Quality Assurance or Quality Engineering, including experience in a Senior QA or QA Lead role.
Hands-on experience with E2E, regression, exploratory, and API testing across web applications, microservices, event-driven architectures, and complex business systems.
Experience validating complex business workflows, pricing configurations, customer entitlements, and complete customer journeys.
Experience owning quality readiness and release decisions, including production monitoring, post-production validation, and risk-based decision making.
Working knowledge of SQL for data validation and defect investigation, along with experience using tools such as Postman, Swagger, mocking tools, and test management systems.
Strong understanding of Agile/Scrum methodologies and CI/CD practices.
Experience using AI tools to improve test design, scenario generation, defect triage, and regression planning, combined with the judgment to validate AI-generated outputs.
Experience building scalable QA processes, automations, or AI-assisted workflows that improve quality and team efficiency.
Strong communicator and collaborator. You know how to influence stakeholders, challenge assumptions constructively, and build alignment across Engineering, Product, and QA teams. You're comfortable leading initiatives and driving outcomes, even without formal authority.
Self-driven and accountable. You take ownership from start to finish, proactively identify risks, and move initiatives forward with minimal guidance. You work well in fast-changing environments and bring a practical, solu המשרה מיועדת לנשים ולגברים כאחד.
 
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27/08/2026
חברה חסויה
Location: Ramat Gan
Job Type: Full Time and Hybrid work
we are looking for a MLOps Team Lead.
As an MLOps Team Leader , you will own our AI infrastructure and backend engineering efforts, leading a team at the intersection of systems design and machine learning to build the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features.
What Youll Be Doing:
Lead MLOps Engineering: Own the roadmap and execution for a team of backend and AI infrastructure/MLOps engineers, setting technical direction, removing blockers, and holding the bar on delivery quality.
Build Production AI Systems: Design and implement production-grade, end-to-end AI solutions, including agentic workflows, that integrate Deep Learning models and Computer Vision algorithms into real features. Own the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Architect Data Platforms: Drive the design and implementation of scalable data platforms and pipelines that power AI capabilities reliably and with an eye on cost and scale.
Cross-functional Collaboration: Work closely with the Algorithms and Data teams to tackle complex, real-world problems, translating research into shippable, maintainable systems.
Elevate Engineering Standards: Champion Software Engineering and System Design best practices across the group, introducing the right methodologies, tooling, and culture of craft.
Who You Are:
Requirements:
Professional Experience: At least 5 years of hands-on Software Engineering experience, with a minimum of 2 years in a team lead or managerial role.
Technical Proficiency:
Production Systems and DevOps: Proven experience building high-scale, production-grade systems on a cloud platform (AWS preferred), with solid command of DevOps practices including CI/CD, containerization, and observability.
Programming: Strong command of at least one programming language, with Python or Rust being a strong advantage.
AI/ML Systems: Solid understanding of the ML model lifecycle, including training, evaluation, deployment, and monitoring, with enough hands-on exposure to make good infrastructure decisions around it. Experience with TensorFlow, PyTorch, or Computer Vision concepts is an advantage.
AI-Augmented Development: Hands-on experience integrating AI coding tools into engineering workflows, with a genuine interest in expanding their use across the team.
Data Engineering: Hands-on experience with data pipelines and big data infrastructure.
Leadership and Mindset:
Engineering Quality: You hold a high bar for correctness, reliability, and maintainability, and you treat quality as a first-class engineering concern, not something retrofitted at the end of a sprint.
Team Builder: A people-first approach to leadership. You coach, you unblock, and you build psychological safety alongside technical excellence.
Engineering Judgment: A strong ability to self-learn, cut through ambiguity, and land well-reasoned technical decisions under pressure.
This position is open to all candidates.
 
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07/09/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
We are looking for a hands-on QA & Automation Team Lead who embodies ambition and positivity.
Someone who can passionately take ownership of quality across our high-level software, lead by example, and collaborate effectively with remote teams to not only meet but exceed our objectives and fulfill the evolving needs of our expanding customer base.
Responsibilities:
- Own the quality and test automation strategy across QM's high-level software, including our SDKs, APIs, user-facing tools, and the services around them.
- Lead a team of QA and automation engineers - setting technical direction, mentoring, and growing the team's capabilities while staying hands-on.
- Design, build, and maintain robust automation frameworks and the test suites that run within our CI flows, validating functionality, performance, and stability.
- Define test plans, coverage goals, and quality gates in close partnership with R&D, architecture, and product teams.
- Partner with DevOps to integrate test suites into the CI/CD pipelines they own, ensuring quality gates are well-defined and effective.
- Own Tier 2 customer support for software issues - investigating escalations, reproducing and diagnosing problems, driving them to resolution, and feeding insights back into test coverage and product quality.
- Drive root-cause analysis and continuous improvement of test reliability, flakiness, and release confidence.
- Establish metrics and reporting that give the organization clear, actionable visibility into product quality and release readiness.
Requirements:
At least 5 years of hands-on experience in software QA and test automation, including 2+ years leading engineers - Must.
Strong programming skills in Python (or equivalent) for building automation frameworks - Must.
BSc. in Computer Science, Computer Engineering, or a relevant scientific field (advanced degrees are an advantage) - Must.
Proven experience designing and maintaining automated test suites and frameworks for high-level software (SDKs, APIs, services) - Must.
Experience handling escalated technical support or working directly with customers on complex software issues - Advantage.
Experience working in a multidisciplinary environment - Advantage.
Experience testing complex systems with demanding performance or reliability requirements - Advantage.
A motivated and resourceful problem solver with a passion for tackling complex technical challenges and raising the quality bar across teams.
This position is open to all candidates.
 
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30/08/2026
חברה חסויה
Location: Ramat Gan
Job Type: Full Time
Were seeking a Solutions Engineer Manager who thrives in fast-paced, customer-facing environments and enjoys leading high-performing engineering teams, delivering complex enterprise integrations, and turning custom technical solutions into scalable, repeatable processes.
About the role
Our delivery org is scaling fast. Customers are getting larger and more global, and the number and complexity of delivery projects is growing with them.
We're hiring a Solutions Engineer Manager to lead the engineers who build the two-way integrations connecting our company's agents to our customers' enterprise systems - and to turn that work from a series of custom projects into a repeatable engine.
Where you own and where you partner. Technical Project Managers own the project plan and the customer-facing schedule. You own the execution: the estimates your team commits to, the quality of what ships, and the health of what runs in production. When a date is at risk, the TPM manages the customer conversation; you own the engineering path back to green.
How the team grows. You'll lead and hire a team of 4-8 Solutions Engineers. Within your first year we expect the charter to broaden into DevOps and product-adjacent engineering, and we expect you to define that team and hire it. If you want to build an org rather than inherit one, this is the job.
This is a Tel Aviv-based role, with travel to our US office and to global customers.
‍What you'll own
The team
Hire, coach, and grow the Solutions Engineering team - then expand it into DevOps and dev hires as the charter widens
Run the day-to-day: capacity allocation across concurrent projects, escalation triage, on-call rotation, 1:1s, and growth plans
Raise the skill ceiling of every engineer who reports to you
Execution
Stand behind your team's estimates - and hit them
Own the quality of shipped integrations and the health of production environments; keep escalations that reach our company personnel low
Build reproducible playbooks so each implementation costs less than the last
Feed engineering reality into TPM and Solutions Architect planning for POCs and production rollouts
Customers
You are not the account owner. You're in the room for four things: consultation, architecture planning, execution excellence, and timelines.
Advise across the full stakeholder range - from the engineers your team integrates with, to their engineering managers, up to directors, VPs of Engineering, and CIOs
Lead architecture planning with customer technical teams: what we'll build against, what their systems can actually support, and where the risk sits
Speak to execution and timelines with authority - what's committed, what it depends on, and what changed. The depth adjusts to the audience; the answer doesn't.
Be the technical voice customers trust when the question is can this actually work
Technical bar
Your engineers will go deeper than you in specific areas. You need enough depth to review their work, make architecture calls, and interview well across all of it.
Large-scale resilient two-way integrations against custom enterprise APIs - queues, retries, idempotency, race conditions, rate limits and quotas
Designing and consuming APIs for enterprise customers. Required knowledge: Protocols (REST, GraphQL), API security & authentication, architecture (polling, webhooks, pagination). Knowledge of best practices for market integrations
Cloud deployments at scale - CI/CD, observability, and running on-call for an independent team. Enough infrastructure judgment to hire DevOps engineers, not just work alongside them.
A plus: on-prem environments; AI, LLM, and knowledge-pipeline engineering; building products and processes under data-protection regulation.
דרישות:
Crazy personal drive. Be a bulldozer.
Insatiable creativeness. Be a big dreamer.
You've led an engineering team to predictable delivery - stable output, dates that hold
You turn one-off solutions into repeatable process by i המשרה מיועדת לנשים ולגברים כאחד.
 
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8801940
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
18/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
We are seeking a Staff Developer to join our team and take a lead role in shaping the architecture, evolution, and reliability of our systems core services.
You will directly shape Apono's technical direction, keeping our architecture aligned with company strategy while pushing forward what's possible in access management and engineering excellence. This role means owning a roadmap that raises the bar on quality, scalability, and security across our platform, as we bridge the operational security gap for organizations running in the cloud.
What you can expct:
Shape the architecture and long-term technical direction of core services powering Apono's platform.
Own complex, ambiguous initiatives end-to-end, from problem definition through rollout, spanning one or more teams and systems.
Break down large, undefined problems into a coherent execution plan, and drive that plan to completion.
Partner with product, design, and other engineering teams as a technical authority, translating ambiguity into clear architectural decisions.
Balance rapid iteration with long-term system health, scalability, and security.
Raise the bar for engineering standards, code quality, observability, and operational excellence across the org.
Mentor senior and mid-level engineers through design reviews, technical deep-dives, and pairing.
Evaluate new technologies and propose architectural improvements that shape how Apono builds going forward.
Leverage AI-assisted engineering workflows to multiply your own impact and the team's.
See your technical decisions directly shape the platform's ability to scale with the business.
Requirements:
8+ years of experience as a backend software developer, with a track record of owning large-scale production systems.
Proven experience architecting and evolving distributed systems, not just building within them.
Deep experience with cloud-native architectures (microservices, Docker, Kubernetes) at scale.
Strong systems thinking - able to reason about trade-offs across performance, reliability, and security.
Demonstrated ability to lead complex, cross-team technical initiatives from ambiguity to delivery.
A track record of raising technical standards beyond your immediate team.
Ability to balance deep technical ownership with business and product outcomes.
Nice to have:
Hands-on experience in identity and access management.
DevOps or platform engineering technical leadership background.
In-depth experience with cloud service providers, mainly AWS.
Strong security mindset.
Experience mentoring engineers into senior or staff-level roles.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8787464
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דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
02/09/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for our **first Forward Deployed Engineer**. You'll sit directly with our customers' engineering teams and get their workloads onto Impala - from the first scoping conversation to a production endpoint carrying real traffic, at a cost and latency profile they couldn't hit anywhere else.
This is an engineering role. You will write code every day, in customer repos and in ours. It also carries pieces of solutions architecture, product management, and pre-sales, and you should want that mix rather than tolerate it. Ambiguous business goals come in; observable, benchmarked, production services go out.
As the founding FDE you also define the function: what a POC looks like, what we promise and measure, which patterns get productized, and how the field feeds the roadmap. The next FDEs will work from what you build here.
What You'll Do
- **Own customer outcomes end to end:** problem framing, evaluation design, migration, deployment, benchmarking, monitoring. You're the technical owner from first call through expansion.
- **Win the POC:** turn a vague objective into a tight spec and a working proof of concept fast, with explicit quality, latency, throughput, and cost-per-token targets - and hit them.
- **Tune serverless inference for real workloads:** model and engine selection, batching strategy, KV cache behavior, speculative decoding, quantization, parallelism, cold-start and autoscaling behavior under bursty traffic. Diagnose regressions down to the inference engine.
- **Migrate workloads onto Impala:** move customers off OpenAI-compatible APIs, self-managed vLLM, SageMaker, or their own GPU fleets - and prove out the quality and cost delta with numbers.
- **Guide model strategy:** advise on open-weight model selection, distillation, and fine-tuning for specific tasks; help customers get from a general-purpose frontier model to a smaller, faster, cheaper one that holds quality.
- **Close the product loop:** bring the field back into the roadmap - write the PRDs, land the PRs, and turn one-off customer work into platform features.
- **Be the technical anchor in the room:** support sales on complex evaluations, run technical onboarding, earn trust with staff engineers and CTOs.
Requirements:
- **4+ years** building and shipping production software
- **Inference in production:** hands-on experience serving LLMs with **vLLM, SGLang, TensorRT-LLM** or equivalent, and real intuition for what makes inference fast or expensive.
- **Optimization fundamentals:** working knowledge of batching, KV cache, quantization, speculative decoding, tensor and pipeline parallelism - and the tradeoffs between them.
- **Model judgment:** fluency with the open-weight model landscape and good instincts on model selection for a given task, hardware profile, and latency budget.
- **Production cloud comfort:** containers, Kubernetes, observability, CI/CD. You don't need to be an SRE, but nothing here should be a black box.
- **Range in the room:** you can hold a technical conversation with a skeptical staff engineer and a commercial one with their VP, in the same meeting.
- **Default ownership:** ambiguity, unfamiliar codebases, and a customer waiting on you are the normal conditions of this job, not exceptions.
- Prior forward-deployed, solutions architecture, or applied ML engineering experience at an infrastructure company.
- Post-training experience: LoRA, SFT, DPO, RLHF, GRPO, distillation.
- GPU-level performance work CUDA, Triton, memory bandwidth and throughput profiling.
- Experience selling into or building for regulated, data-sensitive enterprises.
- Open-source contributions to inference or serving projects.
- You've been the first or second person in a function before.
This position is open to all candidates.
 
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עדכון קורות החיים לפני שליחה
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8807348
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