Summary: We are seeking a Lead AI Engineer to build a central GenAI Platform, leading full-stack agent and platform component development, strengthening CI/CD and observability, and driving delivery across domains. Highlights: 1. Lead development of a central GenAI Platform 2. Build full-stack AI agents and platform components 3. Drive architecture decisions and mentor engineers We are building a central GenAI Platform and need a Lead AI Engineer to help hundreds of product teams ship safe, scalable AI agents faster. You will build full\-stack agent and platform components, strengthen CI/CD and observability, and lead delivery across domains—apply now. **Responsibilities** * Design and build full\-stack applications, AI agents, and platform components that support fast GenAI agent development, validation, and deployment * Create developer tools, CI/CD pipelines, and observability features to enable safe and efficient iteration, including evaluation systems, canary releases, rollout/rollback mechanisms, and cost and quality monitoring * Apply secure software development lifecycle (SDLC) and privacy\-by\-design principles, such as threat modeling and least privilege access * Collaborate closely with product managers, UX designers, and domain experts to deliver customer\-focused solutions with measurable results * Implement current LLM patterns, including retrieval\-augmented generation (RAG), retrieval, routing, tool\-use, and evaluation strategies, to create faster, more reliable AI systems, reduce time\-to\-decision, improve trust and safety, and lower cost per query * Lead hands\-on by driving architecture decisions, mentoring engineers, and owning large\-scale projects **Requirements** * Minimum 5 years of professional experience in software engineering * At least 1 year of experience leading and managing development teams * Demonstrated ability to deliver software products independently or as part of a small, agile team * Experience taking AI agents from concept to production, including safety assessments, iterative testing such as A/B testing, and ongoing improvement * Hands\-on experience with LangChain or LangGraph, MCP, vector databases or RAG systems, and OpenSearch * Background in traditional machine learning tasks, including model training, deployment, and monitoring * Familiarity with regulatory standards such as SOC2 and HIPAA * Excellent problem\-solving skills, strong sense of ownership, and effective cross\-functional communication * Advanced full\-stack development abilities and experience with cloud platforms like AWS, Azure, or GCP * Proficiency in CI/CD practices and Infrastructure as Code * Knowledge of Site Reliability Engineering (SRE) principles * Experience with quality engineering and testing strategies * Understanding of secure SDLC and privacy by design * Proficiency in TypeScript * Fluent English communication skills, both written and spoken, at B2\+ level or above **Nice to have** * Strong understanding of how large language models (LLMs) work, including common failure modes * Practical experience with fine\-tuning and model adaptation techniques