We are seeking a dynamic, forward-thinking Lead AI / ML Engineer to spearhead enterprise-wide adoption of AI-powered tools, workflows, and practices across both internal operations and client delivery teams. This strategic leader will partner with our internal AI Lab, delivery teams, and back-office functions (Finance, HR, Recruiting, BD) to identify high-impact AI use cases, select or build fit-for-purpose tools, and train teams on their use to drive measurable gains in efficiency, quality, and innovation.

The ideal candidate brings strong hands-on knowledge of today’s AI tools and platforms (including GenAI, MLOps, RAG, AutoML, LLMOps, and orchestration frameworks) and combines that technical acumen with a change agent’s mindset—capable of translating potential into real-world outcomes across diverse functions like software development, CI/CD infrastructure, HCD workshop synthesis, data engineering, AI/ML development, and business operations.

You’ll be helping transform a fast-moving technology company with deep federal roots, a collaborative culture, and a commitment to innovation. Our AI Lab, AI and Data Exploitation team, and HCD experts are ready to work with you. You’ll serve as the bridge, ensuring cutting-edge AI capabilities are used not just by technologists, but by every part of the enterprise.

Your key contributions include:

Strategy & Roadmapping

Define and continuously refine the AI Enablement Roadmap for internal teams and delivery domains
Identify high-leverage areas where AI tooling can dramatically reduce effort, increase quality, or accelerate timelines
Collaborate with internal AI Lab, AI & Data Exploitation, Salesforce, Cybersecurity, and DevSecOps leads to align technical solutions with transformation goals

Tooling & Platform Enablement

Evaluate, prototype, and deploy AI tools to enhance workflows in software engineering, data analytics, design research, cybersecurity, business operations, and more
Lead integration of tools such as GitHub Copilot, CodeWhisperer, Claude, ChatGPT Enterprise, LangChain, Bedrock, Vertex AI, Salesforce Einstein GPT, and others
Drive internal adoption of AI-enhanced CI/CD pipelines, documentation assistants, design synthesis tools, and domain-specific copilots

Change Management & Enablement

Develop and deliver training sessions, onboarding content, and office hours to help teams adopt new AI-powered workflows
Act as the primary change agent, embedding with teams during rollouts to encourage adoption and refine tools based on feedback
Evangelize success stories across the organization to build momentum and executive buy-in

Client Delivery Innovation

Support delivery teams in embedding AI-enabled components into client work, e.g., automated testing, generative UIs, smart data pipelines
Ensure internal gains in AI adoption translate into competitive delivery advantages and IP for client engagements

Measurement & Governance

Define KPIs to track efficiency gains, quality improvements, and AI adoption across teams
Collaborate with TechOps and Legal teams to ensure responsible and compliant use of AI tools

Ability to hold a position of public trust with the US government.
Bachelor’s, Master's, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

5+ years of experience in technical delivery, software engineering, data science, platform architecture, or AI/ML development roles
3+ years of direct experience with modern AI tooling and practices, such as:

Generative AI platforms (OpenAI, Anthropic, Claude, Gemini, etc.)
LLM frameworks and RAG (LangChain, LlamaIndex, Bedrock, Vertex AI)
MLOps, LLMOps, or CI/CD automation with AI integration
Embedding-based search, prompt/context engineering, custom fine-tuning

Demonstrated success in leading cross-functional change across technical and non-technical teams
Excellent communication and facilitation skills—capable of training engineers, briefing executives, and co-creating with designers
Experience with AI safety, evaluation, red teaming, and responsible use in production environments
Familiarity with federal government IT environments, security requirements, and cloud platforms (AWS, GCP, Azure)

Preferred Qualifications

Experience standing up or working in an internal AI Lab, AI COE, or Innovation Hub
Familiarity with Human-Centered Design techniques and understanding of how to integrate AI into HCD workflows (e.g., persona generation, sticky note clustering, synthesis)
Experience working in or supporting technical delivery in domains such as DevSecOps, Salesforce, Cybersecurity, or AI and Data Exploitation
Experience with internal platform or product development for employee-facing AI tools (copilots, automations, agents)
Familiarity with secure AI implementation in regulated or compliance-heavy environments
Certifications in AI/ML, cloud platforms, or Agile delivery