Senior AI Lead
LMI Consulting · Tysons, VA, US
About this role
## Overview LMI is seeking a **Senior AI Lead** to support **Department of Veterans Affairs (VA)** modernization initiatives involving **artificial intelligence, automation, data, and digital workflow transformation**. This is a **full-time** role providing senior technical leadership for AI-enabled solutions—from discovery and feasibility through prototyping, evaluation, deployment readiness, and iterative improvement. You will help ensure AI capabilities are **mission-aligned, technically sound, measurable, secure, supportable, and appropriate** for the users and workflows they serve. ## Responsibilities - Serve as the **senior technical lead** for AI-enabled solution delivery (problem framing → feasibility → prototype → evaluation → deployment readiness → iterative improvement). - Translate VA mission and workflow needs into **AI solution approaches, technical requirements, evaluation criteria, and delivery roadmaps**, accounting for **data, security, privacy, user, and operational constraints**. - Lead technical design decisions for **generative AI, retrieval-augmented generation (RAG), agentic AI, intelligent automation, and AI-enabled decision support**. - Guide selection of **models, AI services, orchestration frameworks, retrieval approaches, prompt patterns, agent tools, APIs, and cloud services** based on **mission fit, risk, performance, cost, and maintainability**. - Define AI evaluation approaches covering **task success, groundedness, relevance, error modes, hallucination risk, latency, cost, safety, human review, and release criteria**. - Partner with data and domain teams to assess **authoritative sources, retrieval quality, data readiness, lineage, access constraints, sensitivity, and fitness for AI-enabled use**. - Coordinate technical execution across **software development, data, platform/DevSecOps, integration, QA, HCD/product, cybersecurity/privacy, and governance/architecture** so AI components function as an end-to-end solution. - Establish practical **human-in-the-loop, feedback, guardrail, fallback, escalation, and monitoring** patterns—especially for consequential operational or clinical-adjacent workflows. - Provide senior review of AI prototypes/implementations; identify material risks early and drive remediation before pilot/release/scale decisions. - Partner with platform/DevSecOps on **deployment, secrets, logging, observability, versioning, performance, reliability, model/config management, and operational support**. - Monitor AI solution economics and advise on **model choice, caching, routing, token use, infrastructure, and reuse** to improve cost efficiency without compromising outcomes. - Communicate technical findings, tradeoffs, risks, and recommendations to **VA stakeholders and LMI leadership**; mentor staff and establish reusable AI engineering/evaluation/documentation practices. ## Qualifications - **Bachelor’s degree** in computer science, software engineering, data science, artificial intelligence, information systems, engineering, or related field (equivalent experience considered). **Advanced degree valued**. - **10+ years** progressive experience across software engineering, solution architecture, cloud engineering, data/AI systems, and technical delivery for complex enterprise solutions. - **3+ years** recent hands-on or technical-lead experience delivering **AI/ML, generative AI, LLM, agentic AI, or AI-enabled automation** beyond isolated proofs of concept. - Demonstrated ability to t
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