What is the project, and why should you care? We are looking for an AI Engineering Tech Lead to drive the design and delivery of AI agent systems and multi-agent architectures. This is a technical leadership role combining deep hands-on engineering with technical leadership — guiding architectural decisions, mentoring engineers, and maintaining high standards across the codebase. You will be an excellent fit for this position if you have: * 5+ years of experience in software engineering with a strong focus on AI/ML systems * Expert-level Python skills, including async programming and design patterns. * Demonstrated experience building AI agents and multi-agent systems using LangChain and LangGraph. * Strong practical knowledge of LLM integration patterns: prompt engineering, function/tool calling, retrieval-augmented generation (RAG), embeddings, and vector search. * Extensive experience with cloud platforms — AWS and/or Azure — including deployment, scaling, and management of AI workloads. * Solid general ML foundation: understanding of model training, evaluation, inference pipelines, and the broader ML development lifecycle. * Strong CI/CD pipeline expertise. * Hands-on experience with containerization and orchestration in production environments. * Practical experience with infrastructure-as-code tools for managing cloud resources reliably and repeatably. * Experience implementing AI observability. * Proficiency in using AI tools for everyday tasks (Claude Code, Cursor, Advanced prompting, etc) * Experience designing and building robust APIs (FastAPI, Flask, or similar) and integrating them into larger system architectures. * Proficiency with SQL and NoSQL databases. * Ability to lead technical discussions, conduct meaningful code reviews, and mentor team members. * Upper-Intermediate English or higher.
Would be and advantage: * High knowledge of core ML frameworks * Hands-on experience with AWS SageMaker and broader AWS ML ecosystem. * Solid understanding of the full ML lifecycle.
Here are some of the things you’ll be working on: * Lead the technical design and architecture of AI agent platforms and multi-agent workflows built on LangChain and LangGraph. * Hands-on development of AI agents. * Integrate LLMs from providers such as OpenAI, Anthropic, and Azure OpenAI into production-grade agent pipelines. * Build and optimize CI/CD, containerization, and infrastructure-as-code practices for the team. * Establish and maintain AI observability across agent systems — tracing execution paths, monitoring performance, tracking costs, and surfacing anomalies. * Mentor and guide engineers through code reviews, architectural discussions, and knowledge sharing sessions. * Collaborate with product managers, solution architects, and stakeholders to align technical implementation with business objectives. * Ensure system reliability, scalability, and maintainability through clean architecture, automated testing, and deployment best practices. * Contribute to defining engineering standards, development workflows, and documentation practices across the team. * Contribute to technical solutions for AI-oriented proposals during pre-sale cycles
