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Required AI Engineering Team Lead - Applied AI Engineering Group
Tel Aviv Full-time
The Dream Job
It starts with you - a technical leader driven to build both the agentic AI platform and the engineering team behind it. You care about backend quality, platform reliability, and growing engineers through real ownership. We are AI-first across the board - every team builds and operates agents. You'll set the technical direction for the platform that makes this possible: agent orchestration frameworks, LLM gateways, evaluation infrastructure, tool-calling systems, and retrieval pipelines. Without this platform, agents don't ship - you own the layer that turns AI research into Sovereign AI products, deployed across cloud and on-prem environments. You stay close enough to the codebase to debug production incidents, unblock your engineers, and make sound architecture calls.
If you want to make a meaningful impact, join our mission and lead the team that builds the agentic AI platform driving Sovereign AI products - this role is for you.
The Dream-Maker Responsibilities
Architect and evolve the AI platform - agent orchestration, LLM gateways, context engineering pipelines, evaluation infrastructure, tool-calling systems, and retrieval pipelines - through RFCs, prototypes, and design reviews.
Lead and grow a small team of AI Engineers building the agent framework, production backend services, and AI platform infrastructure - hire, mentor, pair on hard problems, and raise the bar through hands-on code and design reviews.
Contribute to critical systems, debug production incidents, and maintain enough codebase context to make sound technical calls.
Own reliability across AI and agent services - set and enforce SLAs, build observability for non-deterministic systems, and harden tool execution environments for cost and security.
Set the standard for AI engineering practices - agent testing strategies, evaluation frameworks with human-in-the-loop oversight, retrieval quality benchmarks, and CI/CD for AI systems.
Work closely with ML Platform, Data Platform, DevOps, Data Science, and Product teams across the Applied AI Engineering group - ensure the AI platform evolves to serve teams building agentic workflows across the organization.
Measure and improve developer experience - deploy friction, onboarding time, CI turnaround - as seriously as system performance.

Were looking for an Engineering Team Lead, who will be responsible for the foundational infrastructure framework used by all engineering teams to build, deploy, and operate AI agents safely in production. We are building the "operating system" for AI , covering agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. You will lead a high-impact team of 3-4 engineers to create the runtime and platform that defines the future of autonomous enterprise intelligence.
Youll Own:
Agentic Framework Architecture: Designing and building 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 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.

We need an experienced Team Lead who has managed developers before and knows how to get things done. You'll own the delivery and day-to-day leadership of a 7-person team working across two demanding domains - AI and Connect.

Beyond managing the team, you'll be expected to lead the vision. That means staying ahead of the AI curve, identifying where the product should go next, and actively pushing for innovation - not waiting to be told. The team works with LLMs, RAG pipelines, integration infrastructure, and APIs. You need to own the technical design decisions, set the architectural direction, and ensure the team is building things the right way - not just on time.

You'll report directly to the Director of the Growth Group and work closely with Product, Architecture, and peer engineering leads.

What You'll Do
Lead and Develop Your Team - Manage a team of 7 developers across the AI and Connect domains. Run 1:1s, set clear goals, support growth, and create a culture of ownership and accountability.
Drive Delivery - Own the team's roadmap execution. Ensure features are designed well, delivered on time, and meet a high-quality bar.
Own the Architecture - Lead system and feature design end-to-end. Define the architectural approach, review technical designs, and make sure the team builds solutions that are scalable, maintainable, and aligned with the platform's direction.
Champion AI Innovation - Stay sharp on the latest in LLMs, RAG, and AI tooling. Help the team identify opportunities to push the product forward and maintain our competitive edge.
Collaborate Cross-Functionally - Work closely with Product Managers, other TLs, and stakeholders to align priorities and turn vision into execution.
Raise the Bar - Establish and enforce engineering best practices: code quality, automated testing, CI/CD, and microservices design principles.
Recruit When Needed - Participate in hiring as team needs evolve, and help onboard new team members effectively.