Lead Generative AI Engineer

About the role

We are seeking an experienced technical lead to design, build, and scale Generative AI and agentic solutions in a complex enterprise environment. This role combines hands-on engineering, solution architecture, and technical leadership, with a focus on moving AI solutions from proof of concept into secure, reliable production systems.

Responsibilities

• Lead the architecture and development of Generative AI, Retrieval-Augmented Generation, and agentic AI solutions.
• Build and scale AI applications from prototype through production deployment.
• Design secure, scalable integrations across cloud, data, and enterprise platforms.
• Develop RAG pipelines, multi-agent workflows, APIs, and microservices.
• Establish engineering standards, conduct code reviews, and mentor technical teams.
• Implement CI/CD, MLOps, automated testing, monitoring, and observability.
• Evaluate AI solutions for quality, hallucinations, latency, reliability, and cost.
• Partner with business, architecture, security, and data teams to translate requirements into technical solutions.
• Implement responsible AI guardrails related to privacy, security, bias, and human oversight.
• Create reusable AI components, frameworks, and development standards.

Requirements

• 6+ years of experience in software engineering, data engineering, machine learning engineering, or a related field.
• Proven experience deploying and supporting AI or machine learning solutions in production.
• Strong experience with Generative AI, large language models, RAG, prompt engineering, and context engineering.
• Advanced proficiency in Python.
• Experience with GCP, AWS, Azure, or a comparable cloud platform.
• Experience with APIs, microservices, containerization, Docker, and Kubernetes.
• Knowledge of CI/CD, ML Ops, LMOps, monitoring, and AI evaluation practices.
• Demonstrated ability to lead technical teams and communicate with senior stakeholders.

Preferred Qualifications

• Experience with Google Cloud Platform and Vertex AI.
• Experience with Palantir Foundry.
• Experience building AI agents using Lang Graph, Agent Development Kit, or custom frameworks.
• Knowledge of traditional machine learning techniques, including classification, regression, and clustering.
• Experience designing hybrid AI solutions that balance accuracy, performance, latency, and cost.