דרושים » הנדסה » Solutions Engineer

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.

Were looking for our first Forward Deployed Engineer (FDE) to join our company and help build this function from the ground up.
This is a highly technical, hands-on, and customer-facing role. Youll be based in Israel, working closely with our Product and Engineering teams, while traveling regularly across the U.S. to work on-site with our enterprise customers.
Youll work directly with customers to understand their business processes, technical environments, and operational challenges, and translate them into AI-powered solutions. Youll own projects end-to-end - from discovery and requirements gathering through technical design, development, deployment, adoption, and continuous improvement.
As our first FDE, youll have a unique opportunity to define how our company works with customers from a technical perspective, build the processes and best practices for this function, and play a key role in how we scale customer delivery.
Were looking for a strong engineer with a product mindset who enjoys navigating ambiguity, working directly with customers, and turning complex business problems into scalable technical solutions.
our Values
Ownership - We take responsibility and move decisively.
Clarity - We simplify complexity to deliver meaningful impact.
Accuracy - Precision matters in everything we do.
Velocity - We move fast and execute with purpose.
Partnership - We succeed by working closely together.
What Youll Do
Partner directly with enterprise customers, both remotely and on-site across the U.S., to deeply understand their business processes, technical architecture, data flows, and operational challenges.
Lead technical discovery sessions, gather business and product requirements, and translate complex customer needs into scalable AI-powered solutions.
Design, build, configure, and deploy production-ready AI agents, integrations, and workflows that operate reliably within customer environments.
Work hands-on with APIs, enterprise systems, structured and unstructured data, and customer infrastructure to deliver end-to-end solutions.
Own customer engagements from technical discovery through implementation, deployment, adoption, and continuous optimization.
Validate solutions using real customer data, troubleshoot technical challenges, and continuously improve system performance and business outcomes.
Drive measurable business impact by identifying new use cases, increasing platform adoption, and helping drive growth and expansion within customer accounts.
Work closely with Product and Engineering in Israel to influence product direction based on customer feedback, implementation learnings, and real-world use cases.
Act as the technical owner throughout the customer engagement, building trusted relationships with both technical and business stakeholders.
Create reusable implementation playbooks, tools, and best practices that help scale the FDE function as our company grows.

We are looking for a Staff Engineer to join our Core Engineering group. The group is responsible for the real-time, low-latency infrastructure that powers our fraud decisions and external APIs.

In this role, youll work on core backend components such as our decision engine, ingestion and enrichment pipelines, schema management systems, and self-serve API platform. The software you build will power critical business decisions and directly serve some of the worlds largest merchants.

This is a high-impact, high-ownership position for an engineer who thrives on solving complex distributed systems challenges, cares deeply about production-grade quality, and wants to shape the foundation of our decisioning platform.


What you'll be doing:
Design, build, and scale backend systems that power our real-time decisioning and APIs.
Own projects end-to-end - from design and implementation to production rollout and monitoring.
Ensure systems are low-latency, fault-tolerant, and high-throughput across distributed environments.
Enhance observability, reliability, and developer experience through strong operational and tooling practices.
Collaborate with Product, analysts, data scientists, and infrastructure teams to drive innovation across our decision ecosystem.
Participate in technical discussions and customer interactions, providing expertise and clear communication when supporting enterprise integrations.

We are looking for a Senior Software Engineer to join our Core Engineering group. The group is responsible for the real-time, low-latency infrastructure that powers our fraud decisions and external APIs.

Our systems process billions of requests every day, ensuring high availability, security, and performance at global scale.

In this role, youll work on core backend components such as our decision engine, ingestion and enrichment pipelines, schema management systems, and self-serve API platform. The software you build will power critical business decisions and directly serve some of the worlds largest merchants.

This is a high-impact, high-ownership position for an engineer who thrives on solving complex distributed systems challenges, cares deeply about production-grade quality, and wants to shape the foundation of our decisioning platform.


What you'll be doing:
Design, build, and scale backend systems that power our real-time decisioning and APIs.
Own projects end-to-end - from design and implementation to production rollout and monitoring.
Ensure systems are low-latency, fault-tolerant, and high-throughput across distributed environments.
Enhance observability, reliability, and developer experience through strong operational and tooling practices.
Collaborate with Product, analysts, data scientists, and infrastructure teams to drive innovation across Forters decision ecosystem.
Participate in technical discussions and customer interactions, providing expertise and clear communication when supporting enterprise integrations.

We are looking for a Senior II Software Engineer to join the CX Platform team, the foundational engineering team powering our entire Customer Experience group. This is a high-impact, hands-on role at the intersection of backend engineering, AI infrastructure, and customer-facing product.

You'll work across the full platform stack (backend services, data pipelines, security, cost, and scale) with a meaningful and growing focus on AI infrastructure. We own the agentic platform for the entire Product Offering group: from building the LLM infrastructure and agentic workflows to ensuring they're reliable, observable, and safe in production.

What you'll be doing:
Own AI infrastructure for the Product Offering group. Design, build, and evolve the shared AI platform (agentic workflows, LLM integrations, observability, and guardrails) that CX product teams build on.
Ship agentic features end to end. Lead development of AI-driven capabilities using LangChain, LangFuse, and AWS Bedrock, from architecture through production deployment and monitoring.
Drive platform architecture. Set the technical direction for the CX backend (services, data pipelines, API patterns) with an eye for scalability, reliability, and developer experience.
Own core data foundations. Design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, and MySQL; keep pipelines fast, fresh, and reliable.
Mentor and elevate. Help engineers across the CX group grow in backend craft, AI engineering, and system design thinking.
Collaborate cross-functionally. Work with product, design, and customer-facing teams to turn ambiguous problems into well-scoped, high-quality solutions.

We are constantly striving to make our systems reliable, scalable, and simple to operate so our services are available to travelers when they need them most. With our continued growth, we have exciting challenges ahead and we're looking for a Senior Site Reliability Engineer to join our team in Tel Aviv. This role blends classic SRE ownership with pragmatic AI SRE work: you will build and operate the platforms, automation, observability, and incident response practices that keep Navan reliable, while helping teams use AI solutions, AI providers, and their APIs safely and dependably.



This is a hands-on engineering role, not a research role. You will partner with product, platform, data, security, support, and incident response teams to make production systems and AI-powered experiences more resilient. You will use software engineering, infrastructure as code, SLOs, telemetry, provider observability, and automation as your main tools, and you will apply AI where it creates measurable reliability value rather than novelty.



This position is based out of our new Tel Aviv office.



What You'll Do:

Support AI-based application solutions where reliability matters. Partner with the development teams building AI-powered travel experiences to support the development and production operation of their solution.
Work with AI solutions, providers, and APIs. Partner with teams integrating AI capabilities and providers, with attention to API reliability, authentication, quotas, rate limits, latency and provider-specific operational constraints.
Troubleshoot AI tools and provider issues. Diagnose failures across AI-powered workflows, provider APIs, configuration, permission errors, degraded responses and related areas.
Operate reliable production platforms. implement and run cloud infrastructure,and help product teams move quickly without compromising reliability.
Improve observability. Build dashboards, alerts, traces, logs, and runbooks that make service health clear, actionable, and tied to SLOs and customer impact.
Apply AI to SRE workflows. Prototype and productionize AI-assisted systems that create effective and efficient operations
Automate operational toil. Create tools, workflows, and automation that remove repetitive manual work and make operational knowledge easier to use.

Were looking for an Engineering Tech Lead to help drive some of the most strategic technical initiatives at our company. This is not a traditional Tech Lead role. Were looking for someone who is deeply technical and highly hands-on, but also knows how to think strategically, lead architecture decisions, and represent the company in front of enterprise customers and senior stakeholders. Youll work across multiple teams and domains, partnering closely with Platform, Product, and Engineering teams to design and deliver AI-powered enterprise solutions at scale. One moment you might be deep in architecture or code, and the next youll be in a room with customer executives helping guide critical technical decisions. We work on site from our offices in Tel Aviv.
What Youll Do
Lead architecture and technical direction for strategic enterprise AI initiatives
Work directly with some of the worlds largest enterprises to design and deliver scalable AI-powered solutions
Partner cross-functionally with Platform, Product, and Engineering teams across the company
Stay deeply hands-on with the code and engineering teams
Drive complex technical decisions across scalability, reliability, performance, and system design
Help customers solve real production challenges and build long-term technical trust
Design versatile enterprise-grade solutions across different customer environments and use cases
Influence engineering standards, architecture practices, and long-term technical direction
Operate in a fast-moving, high-ownership environment where execution speed matters.

We are seeking a Staff Systems Software Engineer to design and build the foundational infrastructure that powers products used by billions of people worldwide. In this role, you will architect and implement large-scale distributed systems, low-level platform components, and high-performance services that underpin our core product stack. You will drive technical strategy across system reliability, performance, and scalability, partnering closely with product, infrastructure, and data engineering teams to deliver systems that operate at global scale with high availability and efficiency.
Software Engineer, Systems Responsibilities
Architect and implement large-scale distributed systems and platform services that support high-throughput, low-latency workloads across our product infrastructure
Lead the technical design of systems components including storage layers, compute pipelines, networking abstractions, and service orchestration frameworks
Identify and resolve systemic performance bottlenecks through instrumentation, profiling, and targeted optimization across the full systems stack
Define and enforce service level objectives for owned systems, building dashboards, alerting pipelines, and runbooks to reduce mean time to mitigation during incidents
Drive reliability improvements by reducing failure surface, designing resilient rollout strategies, and leading regular resiliency and overload testing exercises
Collaborate with cross-functional partners across product engineering, infrastructure, and data science to align system architecture with evolving product and business requirements
Establish and evolve coding standards, architectural patterns, and engineering best practices for systems development across the broader organization
Leverage AI-assisted development workflows to accelerate design iteration, code generation, and systems analysis, applying sound judgment on when to rely on AI versus deep systems expertise
Mentor other engineers on systems design principles, debugging methodologies, and production operations, and contribute to onboarding programs for new team members
Lead incident retrospectives, identify root causes of complex production failures, and drive implementation of systemic improvements to prevent recurrence

This role sits at the intersection of AI and high-performance systems engineering, focused on solving real-world problems under strict constraints. You will work on systems where performance and reliability are critical and where improvements have a direct, measurable impact on real-world safety.

This is a senior, systems-focused role with end-to-end ownership over performance and reliability of production computer vision pipelines. You will define optimization strategies, identify bottlenecks across the system, and drive improvements under real-world constraints.

What youll do
Build and optimize real-time computer vision pipelines running on edge systems processing live maritime video streams (e.g, NVIDIA Jetson, Triton Inference Server).
Take models from research and turn them into production-ready, reliable components deployed on vessels.
Profile and improve end-to-end system performance across: multi-camera video ingestion; preprocessing; inference; postprocessing
Identify and resolve bottlenecks across CPU, GPU, memory, and pipeline coordination.
Make and justify tradeoffs between latency, accuracy, stability, and resource utilization.
Design and implement robust data and inference pipelines (video -> model -> actionable output for crew).
Develop benchmarking and evaluation workflows to measure performance end-to-end and support release gating.
Build and improve observability tools, including logging, monitoring, and debugging workflows for production systems.
Define and maintain clear interfaces between research code and production systems.
Work closely with research and backend teams to integrate new models into production systems.
Continuously improve system efficiency and reliability under hardware and runtime constraints.

We are looking for a strong Backend Software Engineer to bridge the gap between our Machine Learning research team and our enterprise production systems. You will act as the technical backbone for our ML Scientists - by advising, designing and implementing the production facing features. If you are a backend expert who wants to solve complex system architecture challenges and dive into the world of ML platforms & Agentic LLM pipelines, this is the role for you - An exciting role collaborating with ML science team, data/infra team and DevOps to drive real customer impact.



As a ML Engineer, you will:



Lead ML delivery: transforming research output (code, models, ideas) into robust, scalable, low-latency microservices in production

Help architect e2e solutions to real customer pains ranging from ingestion, integration, ETLs, DB design up to low-latency services

Design, build, and maintain automated workflows for ML models, including auto-trains, benchmarking, testing, performance gating, and production deployment.

Tackle complex backend challenges: optimizing API response times, managing database connectivity and concurrency at scale, balancing accuracys drive for complex questions with the business needs of fast responsiveness by making hard technical trade-offs between customer gains and business costs.

Design and optimize data pipelines and ETL processes, connecting our Snowflake data warehouse to our training environments.

Work within our existing ML infrastructure (Kubeflow, MLflow, KServe) to ensure smooth model lifecycles and performance monitoring.

Collaborate closely with ML Scientists, guiding them on software engineering best practices without slowing down their research.

Monitor and optimize production models for performance, cost efficiency, availability, and observability.