Senior AI Engineer
Role details
Job location
Tech stack
Job description
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 candidate 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.
Contributions
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:
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Strategy & Roadmapping
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Define and continuously refine the AI Enablement Roadmap for internal teams and delivery domains
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Identify high-leverage areas where AI tooling can dramatically reduce effort, increase quality, or accelerate timelines
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Collaborate with internal AI Lab, AI & Data Exploitation, Salesforce, Cybersecurity, and DevSecOps leads to align technical solutions with transformation goals
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Tooling & Platform Enablement
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Evaluate, prototype, and deploy AI tools to enhance workflows in software engineering, data analytics, design research, cybersecurity, business operations, and more
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Lead integration of tools such as GitHub Copilot, CodeWhisperer, Claude, ChatGPT Enterprise, LangChain, Bedrock, Vertex AI, Salesforce Einstein GPT, and others
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Drive internal adoption of AI-enhanced CI/CD pipelines, documentation assistants, design synthesis tools, and domain-specific copilots
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Change Management & Enablement
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Develop and deliver training sessions, onboarding content, and office hours to help teams adopt new AI-powered workflows
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Act as the primary change agent, embedding with teams during rollouts to encourage adoption and refine tools based on feedback
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Evangelize success stories across the organization to build momentum and executive buy-in
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Client Delivery Innovation
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Support delivery teams in embedding AI-enabled components into client work, e.g., automated testing, generative UIs, smart data pipelines
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Ensure internal gains in AI adoption translate into competitive delivery advantages and IP for client engagements
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Measurement & Governance
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Define KPIs to track efficiency gains, quality improvements, and AI adoption across teams
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Collaborate with TechOps and Legal teams to ensure responsible and compliant use of AI tools
Requirements
Required
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Ability to hold a position of public trust with the US government.
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Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
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5+ years of experience in technical delivery, software engineering, data science, platform architecture, or AI/ML development roles
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3+ years of direct experience with modern AI tooling and practices, such as:
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Generative AI platforms (OpenAI, Anthropic, Claude, Gemini, etc.)
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LLM frameworks and RAG (LangChain, LlamaIndex, Bedrock, Vertex AI)
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MLOps, LLMOps, or CI/CD automation with AI integration
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Embedding-based search, prompt/context engineering, custom fine-tuning
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Demonstrated success in leading cross-functional change across technical and non-technical teams
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Excellent communication and facilitation skills-capable of training engineers, briefing executives, and co-creating with designers
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Experience with AI safety, evaluation, red teaming, and responsible use in production environments
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Familiarity with federal government IT environments, security requirements, and cloud platforms (AWS, GCP, Azure)
Preferred Qualifications
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Experience standing up or working in an internal AI Lab, AI COE, or Innovation Hub
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Familiarity with Human-Centered Design techniques and understanding of how to integrate AI into HCD workflows (e.g., persona generation, sticky note clustering, synthesis)
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Experience working in or supporting technical delivery in domains such as DevSecOps, Salesforce, Cybersecurity, or AI and Data Exploitation
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Experience with internal platform or product development for employee-facing AI tools (copilots, automations, agents)
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Familiarity with secure AI implementation in regulated or compliance-heavy environments
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Certifications in AI/ML, cloud platforms, or Agile delivery