AI Tech Lead (2 openings)

About the role

Eurisko is seeking two AI Tech Leads to own the design, development, and delivery of Large Language Model (LLM) and Generative AI solutions. The role blends technical leadership with hands‑on engineering, guiding a team to build secure, scalable AI applications.

Key responsibilities

• Own AI solution architecture and delivery from discovery through deployment and continuous improvement.
• Design LLM applications, Retrieval‑Augmented Generation (RAG) pipelines, AI agents, and integrate them with enterprise data and systems.
• Evaluate and select models, frameworks, and implementation approaches based on quality, security, latency, scalability, and cost.
• Lead and mentor AI engineers, conduct code reviews, and resolve complex technical challenges.
• Establish standards for AI evaluation, automated testing, monitoring, data privacy, and safeguards against unreliable outputs.
• Collaborate with product owners, backend, data, QA, and DevOps teams to deliver complete solutions.
• Drive technical planning, estimation, and delivery within Agile/Scrum teams, managing dependencies and risks.

Required profile

• Strong experience in software or AI engineering with a proven record of leading engineers and delivering production solutions.
• Practical experience building LLM and Generative AI applications, including prompt engineering, RAG, embeddings, vector search, and model integration.
• Solid Python skills and experience designing APIs, backend services, and maintainable architectures.
• Experience assessing AI output quality, diagnosing hallucinations and retrieval issues, and improving reliability.
• Understanding of secure AI development, access controls, sensitive data handling, and prompt‑injection risks.
• Proven experience working in Agile/Scrum environments.

Required skills

• Python
• Large Language Models (LLM)
• Generative AI
• Retrieval‑Augmented Generation (RAG)
• Embeddings & vector search
• API design & backend services
• Secure AI development
• Agile/Scrum methodology
• Docker
• Kubernetes
• CI/CD pipelines
• Cloud platforms (AWS, Azure, GCP)