Lead AI Integration Engineer

Design, build, and deploy intelligent backend services using Python and Azure AI Foundry.

Consume Force Account outputs by API, ensuring the system can accurately display and act on data classification and extraction.

Engineer and optimize Retrieval-Augmented Generation (RAG) pipelines over Standard Operating Procedures (SOPs) to provide contextual, accurate, and actionable insights to users.

Deliver assistive intelligence directly on the case, seamlessly integrating AI outputs into the end-user's workflow.

Design and strictly enforce a redact-before-model discipline, ensuring that all Personally Identifiable Information (PII) is stripped from payloads before data ever reaches a foundational model.

Collaborate with product, design, and engineering teams to shape AI features and translate business goals into technical execution.

Proactively identify AI-driven automation and product improvement opportunities, building prototypes to prove value.

Mentor junior engineers and champion secure, responsible AI coding practices within your team.

Troubleshoot AI-specific technical challenges, including prompt injection risks, model latency, and data leakage.

Guide team members on model selection, evaluation, fine-tuning, and Gen AI usage.

Actively evaluate emerging LLM tooling, agentic frameworks, and open-source developments for applicability to client engagements.

Own the architecture of the team's agentic and LLM systems — agent orchestration, tool integration (e.g., Model Context Protocol), retrieval, and human-in-the-loop design.

Design and implement evaluation frameworks for LLM and agentic systems — covering correctness, boundary, and intent checks — as a standard part of delivery.

Drive adoption of the agentic SDLC across the team: select and roll out AI engineering tools, define usage and governance standards, and measure their impact on delivery velocity and quality.

Establish responsible-AI and evaluation frameworks for agentic systems — guardrails, safety testing, human oversight, and model governance.