דרושים » הנדסה » Software Engineering Team Lead

We are looking for a Technical Lead to drive the architectural direction and engineering excellence of this group. This is a senior, deeply hands-on role for a technology leader who can own the technical roadmap, mentor a team of elite engineers, and build the infrastructure that challenges platform to its theoretical limits.
What You'll Lead:
Define and own the technical architecture of the group's distributed testing and reliability platform - designing for massive scale, real-world workload simulation, and adversarial failure injection
Lead effort involving multiple engineers, setting technical standards, running architecture reviews, driving design decisions, and mentoring engineers to grow
Build the systems that orchestrate millions of concurrent IO operations, inject chaos at the infrastructure layer (latency, packet loss, hardware failures), and expose the hardest-to-find race conditions and consistency bugs
Advance AI-driven approaches to test automation: intelligent scenario generation, LLM-augmented root-cause analysis, and autonomous validation pipelines
Drive observability and reliability engineering across the group - building telemetry pipelines that track P99 latency, jitter, and system health, turning quality into a quantitative discipline
Collaborate deeply with Core R&D, Storage Kernel, and Infrastructure teams - translating architectural knowledge into targeted reliability strategies
Establish engineering practices - design docs, production-grade code reviews, testing philosophy, and cross-team technical alignment

We're hiring the engineering leader who will own its AI core.
Small senior team, greenfield architecture and real production environments from day one. You'll be one of the founding technical leaders - writing code, shaping the architecture, and growing the team as the product scales.
What You'll Do:
Agent Architecture & Engineering:
Design and build the AI systems at the center of the product: researcher agents, deterministic runners, multi-agent orchestration across thousands of targets and hundreds of sites.
Own the full agent stack - LLM selection and behavior, RAG pipelines, tool use, memory, evaluation, and observability. Make architectural decisions that will define how the product works for years.
Drive adoption of the modern agent ecosystem: LangGraph, MCP, semantic tool discovery, hybrid edge/cloud workflows, A2A patterns. Keep pushing the frontier.
Safety & Reliability:
Design for progressive autonomy: pre-checks, fault tolerance, rollback, and full audit trails. In our customers' environments - critical infrastructure, enterprise security - a wrong action has real consequences.
Build the evaluation and observability pipelines that make autonomous agent behavior trustworthy and debuggable in production.
Partner with Security and DevOps on agent execution boundaries, especially across on-prem ↔ cloud data flows.
Technical Leadership:
Spend most of your time in the codebase. Set the technical bar by example - architecture, code quality, and engineering judgment.
Establish standards for testing, evaluation, and safe deployment of AI systems. Build the practices that scale with the team.
Work directly with the PM and enterprise design partners to shape the roadmap. Your decisions will drive the product, not just execute it.
Team:
Start with a small senior group, grow it deliberately. Hire well, mentor, and shape the engineering culture of a startup inside a public company.

We are looking for an MLOps Team Leadto drive the development of an internal machine learning platform for a group of ML teams. This is a hands-on leadership role: you will guide a small team of MLOps engineers that builds the automation and infrastructure powering our research (R&D) workflows and runs our pipelines to production. You will take ownership of end-to-end initiatives and drive the team toward critical infrastructure and model-lifecycle milestones, while staying close enough to the code to set technical direction and raise the bar by example.

You will be responsible for building and maintaining the models and data pipelines behind our data science workflows, ensuring the accuracy, consistency, and efficiency of the data used for training and inference, working across structured and unstructured data from many sources on a large-scale, distributed platform.

WHAT YOU WILL DO

- Lead, mentor, and grow a team of MLOps engineers, owning delivery and technical quality.

- Take end-to-end ownership of infrastructure and pipeline initiatives across the LMM group, from design through production.

- Stay hands-on: contribute to design and code, review work, and set engineering standards.

- Drive the team through critical milestones in ML model-lifecycle and infrastructure ownership.

- Partner with R&D and other stakeholders to translate research needs into robust, scalable systems.

- Help evolve the platform, including our ongoing migration from Dask to Ray.

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.

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer specializing in infrastructure to join our founding team. The focus of this role is to build and scale the infrastructure that powers autonomous AI agents automating complex enterprise workflows. You will own the systems, pipelines, and platforms that let our AI agents run reliably, securely, and at scale in production.

Your Impact
Infrastructure & Platform

Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems.

Build and scale the backend systems that support high-throughput document processing and data extraction workloads.

Cloud Infrastructure and Scalability

Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency.

Own containerization and orchestration (Docker, Kubernetes) for all production workloads.

Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things.

Data Infrastructure

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale.

Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM).

API & Systems Integration

Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software.

Design for reliability: retries, observability, and graceful degradation across distributed systems.

Security and Compliance

Implement authentication and authorization mechanisms (OAuth2, JWT) to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure.

Monitoring and Optimization

Build observability and monitoring systems to track infrastructure health, performance, and cost.

Continuously optimize system performance for speed, reliability, and cost-efficiency at scale.

Collaboration

Work closely with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability.

Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy.

As a Staff Engineer, you will serve as the technical anchor for a critical business domain. Your mission is to look beyond the immediate sprint and shape the long-term architectural vision that allows our product to scale, evolve, and deliver massive value.

You will operate at the intersection of Business Strategy and Deep Tech. You wont just be senior support; you will be a strategic partner to Product Leadership, defining how we solve our biggest problems. You will act as a Force Multiplier-tackling the most complex cross-team challenges while simultaneously elevating the skills, velocity, and quality of every engineer around you.

Key Responsibilities
Own the Technical Vision: Define and drive the architectural roadmap for your product domain. You will anticipate scaling bottlenecks, design resilient distributed systems, and ensure our tech stack supports the next 10x of business growth.
Solve the Hard Problems: Tackle complex, cross-cutting technical challenges that span multiple teams or services-whether its migrating a legacy monolith, optimizing high-throughput data pipelines, or defining new API standards.
Be a Force Multiplier: Mentor Senior Engineers and Tech Leads, helping them grow into the next generation of leaders. You will introduce engineering patterns, tools, and practices that make the entire organization faster and safer.
Partner with Product: Work directly with Directors and VPs of Product to validate feasibility early in the discovery phase. You will translate ambitious business goals into pragmatic technical strategies.
Remain Hands-On: While you lead strategy, you are still a builder. You will code the critical paths, prototype complex solutions, and set the standard for code quality and review.

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.

We're looking for a hands-on Engineering Manager to lead a team of senior engineers owning this space end-to-end, from integration design through production ownership. You'll have real autonomy, a direct line from your team's work to customer outcomes, and room to shape how a technically deep domain is built and run.
What you'll own:
Lead and grow a team of engineers, creating clarity on priorities, raising the technical bar, and building real domain ownership
Own execution end-to-end: integration architecture, technical design, delivery predictability, and the operational health of systems that sync critical financial data at scale
Drive reliability and data correctness, strong debugging and sound judgment around sync semantics, idempotency, error handling, and recovery, plus calm decision-making when something breaks in production
Make sure your engineers understand the business and the ERPs behind the systems, the financial flows and edge cases, not just the code
Translate business goals and the realities of messy, heterogeneous ERP systems into pragmatic technical plans
Partner closely with Product, Operations, Support, and other engineering teams to deliver integrations that balance customer impact, time-to-value, and quality
Coach engineers through feedback, mentoring, and high standards

Were looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.
As a Senior Staff Software Engineer in the Detection Platform group, you will be tasked with being the technical authority responsible for defining and evolving the architecture of the cloud-native systems that power our AI SIEM detection, hunting, and response capabilities, including large-scale real-time detection engines, stateful detection engines, anomaly detections, ML pipelines, agentic SOC and threat-hunting capabilities. You will lead the design and execution of backend systems that process billions of events and several petabytes of data daily and serve tens of thousands of security specialists at enterprise and government customers worldwide. Your technical leadership will bridge long-term architectural strategy and high-velocity product delivery, and you will drive cross-team initiatives that shape how detection and response are built and operated across the group.

As an Application Infrastructure Team Lead, youll spearhead the development of the core frameworks and services that power our entire ecosystem. In this role, youll sit at the vital intersection of application development and systems engineering, ensuring our platform remains resilient, high-performing, and developer-friendly as we scale.
If you are a technical heavyweight who loves Java but thrives on leading teams through complex data and infrastructure puzzles, this is your opportunity to build the foundation for our next phase of growth.
Youll Own:
Team leadership & mentorship: Guiding a high-performing engineering team and fostering a culture of ownership and excellence.
Core application infrastructure: Designing and maintaining mission-critical frameworks using Java and Spring Boot.
Technical standards: Defining and enforcing the benchmarks for code quality, system performance, and security across the entire stack.
Streaming & messaging pipelines: Owning the reliability and scalability of asynchronous communication using Kafka or SQS.
Youll Solve:
Data layer optimization: Leading specialists to tackle challenges in high availability and performance across PostgreSQL, MongoDB, OpenSearch, and Redis.
Distributed systems complexity: Designing robust pipelines for asynchronous communication and data streaming at scale.
Architecture gaps: Bridging the gap between DevOps and Product teams to align infrastructure capabilities with evolving business needs.
Youll Impact:
Engineering velocity: Providing the foundational building blocks that empower all product engineering teams to build faster and better.
System reliability: Ensuring the high availability, scalability, and security of mission-critical systems.
Technical culture: Driving a mindset of continuous improvement and technical excellence that resonates across the R&D organization.