Lead Ai Engineer
Pubblicato il 14-09-2026 - Capco in Catania
OverviewAs 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 / BenefitsComprehensive health agevolazioni coverage
Meal Vouchers
Welfare allowance
Access to internal and Tier 1 learning platforms
ResponsabilitàDesign 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 fondamentali8+ 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