Lead Software AI Engineer

Overview As 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.

Retribuzione / Benefits

Comprehensive health benefit coverage

Meal Vouchers

Welfare allowance

Access to internal and Tier 1 learning platforms

Responsabilità

Design end-to-end architecture for Generative and Agentic AI solutions (orchestration, AI agents, tool/function calling, RAG, memory/state)

Maintain hands-on development, evolving prototypes into production-grade components

Define engineering standards and best practices for AI apps (reference architectures, testing, guardrails, observability, CI/CD)

Architect scalable, secure AI systems considering performance and production requirements

Evaluate and select LLMs, frameworks, platforms, and tools

Lead design and code reviews, mentor engineers, raise engineering standards

Engage with clients to translate business requirements into technical architectures and document trade-offs

Contribute to technical documentation and thought leadership in Generative and Agentic AI

Requisiti fondamentali

• 8+ years in Software/Backend Engineering or similar
• Production-grade Python (or equivalent) coding
• Experience with LLM and Agentic AI applications (agents, orchestration, tool/function calling)
• Strong understanding of RAG, retrieval, vector search
• Experience with agentic frameworks (LangChain, LangGraph, MCP)
• Testing/evaluation of non-deterministic AI systems, monitoring and observability
• Software architecture fundamentals (APIs, distributed systems, integration patterns, production reliability)
• Experience with at least one major cloud platform (AWS, Azure, or GCP) and cloud-native practices
• DevOps practices including containers, CI/CD, IaC and observability
• Ability to communicate complex concepts to technical and non-technical stakeholders
• Fluent professional English
• strong communication and stakeholder management
• mentoring and technical leadership
• client-facing delivery
• Python or equivalent
• LLM orchestration and AI agents
• RAG architectures and vector-based search