Lead Ai Engineer

pAs Lead AI Engineer in Capco AI Lab, you will design and implement production-grade Generative and Agentic AI solutions for financial services clients. You’ll guide architecture, set engineering standards, and remain hands-on to deliver robust systems from prototype to production. You’ll collaborate with clients and senior stakeholders to translate business needs into scalable AI architectures. This is a senior, client-facing role with impact on technology choices and project delivery, in a growth-focused, inclusive environment. /pulliWelfare allowance /liliAccess to internal and Tier 1 learning platforms /liliDesign end-to-end architecture for Generative and Agentic AI solutions (orchestration, AI agents, tool/function calling, RAG, memory/state) /liliMaintain hands-on development, evolving prototypes into production-grade components /liliDefine engineering standards and best practices for AI apps (reference architectures, testing, guardrails, observability, CI/CD) /liliArchitect scalable, secure AI systems considering performance and production requirements /liliEvaluate and select LLMs, frameworks, platforms, and tools /liliLead design and code reviews, mentor engineers, raise engineering standards /liliEngage with clients to translate business requirements into technical architectures and document trade-offs /liliContribute to technical documentation and thought leadership in Generative and Agentic AI /lili8+ years in Software/Backend Engineering or similar /liliProduction-grade Python (or equivalent) coding /liliExperience with LLM and Agentic AI applications (agents, orchestration, tool/function calling) /liliStrong understanding of RAG, retrieval, vector search /liliExperience with agentic frameworks (LangChain, LangGraph, MCP) /liliTesting/evaluation of non-deterministic AI systems, monitoring and observability /liliSoftware architecture fundamentals (APIs, distributed systems, integration patterns, production reliability) /liliExperience with at least one major cloud platform (AWS, Azure, or GCP) and cloud-native practices /liliDevOps practices including containers, CI/CD, IaC and observability /liliAbility to communicate complex concepts to technical and non-technical stakeholders /liliFluent professional English /lilistrong communication and stakeholder management /lilimentoring and technical leadership /liliPython or equivalent /liliLLM orchestration and AI agents /liliRAG architectures and vector-based search /li /ul #J-18808-Ljbffr