Technical Lead AI

As a key member of the First American technology organization, the Technical Lead – AI will act as both a hands-on leader and subject matter expert, responsible for driving the design, development, and delivery of scalable, secure, and cost-effective AI/ML, Generative AI, and Agentic AI solutions leveraging Azure and AWS cloud platforms.

This role operates at the intersection of innovation and enterprise execution, leading teams to build production-grade AI systems that are reliable, well-governed, and aligned with industry standards. The Technical Lead will play a critical role in advancing responsible AI practices across the organization, spanning traditional machine learning to advanced Generative AI and Agentic AI systems, while ensuring robust governance, security, and scalable AI pipelines.

Key Responsibilities:

Lead the design and implementation of end-to-end AI/ML, Generative AI, and Agentic AI solutions.

Drive development of secure, scalable, and cost-optimized AI systems on Azure and AWS.

Provide technical leadership across AI initiatives, guiding teams on architecture and best practices.

Define and enforce AI governance frameworks, safety guardrails, and compliance standards.

Design and implement secure AI pipelines and MLOps workflows.

Lead development of Retrieval-Augmented Generation (RAG) pipelines and hybrid search solutions.

Oversee LLM orchestration, prompt engineering, and agent-based system design.

Establish AI evaluation, monitoring, and performance tracking frameworks.

Collaborate with business and technology stakeholders to translate requirements into solutions.

Mentor engineers and foster a culture of innovation and technical excellence.

Community & Enablement:

Build and grow an internal AI/ML community of practice.

Define and promote best practices across ML, Generative AI, and Agentic AI.

Develop enablement assets, reusable frameworks, and reference architectures.

Technical Skills & Expertise:

Strong programming expertise in Python and machine learning frameworks.

Hands-on experience with Generative AI, LLM orchestration, and agentic frameworks.

Advanced skills in prompt engineering and context management.

Proven experience in MLOps and production AI deployments.

Strong cloud experience (AWS, Azure, or GCP).

Experience with vector databases and retrieval systems.

Deep understanding of RAG architectures and retrieval strategies.

Experience in AI governance, safety, and evaluation frameworks.

Solid foundation in data analytics and data engineering concepts.

Education & Experience:

Minimum 10 years of work experience.

Bachelor’s or Master’s degree in Computer Science or related field.

Extensive experience delivering enterprise-scale AI solutions.

Proven track record of leading AI/ML projects and teams.

Good to Have:

Experience in title insurance or financial services domain.