Director, Applied AI Engineering

3E • Bethesda, MD

1d • $190,000 - $220,000

About The Position

As the Director, Applied AI Engineering, you will lead the team turning powerful AI models and proprietary data into secure, scalable, user-facing solutions. This role reports to the VP, Technology Operations, and works closely with the engineering and product leadership team to build, iterate, and scale AI-powered capabilities that drive measurable customer and business outcomes.
You’ll partner closely with the CTO (a seasoned AI leader and hands-on partner) and establish the engineering foundations (platform, APIs, evaluation, safety, and operations) to deliver expert-led AI at scale. A key part of this role is redesigning and operationalizing an AI-native software development lifecycle that meaningfully accelerates planning, coding, testing, review, and production operations—securely and with strong observability.
You'll be building the engineering organization that defines what AI-first software development looks like - not for a future decade, but for right now. This is your opportunity to architect from first principles, shape how AI amplifies human capability at scale, and leave a lasting imprint on both 3E and the broader industry.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Machine Learning, or a related field or equivalent experience developing and deploying production-grade AI systems and/or SaaS platforms at scale.
• Demonstrated success leading application engineering organizations through meaningful transformation, including measurable improvements in speed, quality, reliability, and team leverage.
• Proven experience re-architecting SDLCs and engineering workflows (CI/CD, quality gates, testing strategy, release practices, observability) to materially improve delivery speed and quality; experience designing or operating AI-native or AI-augmented engineering organizations.
• Deep, hands-on experience developing and deploying production-grade AI systems as a Software Engineer or Machine Learning Engineer (or similar role).
• Hands-on experience with LLMs, generative AI, and agentic frameworks such as MCP, A2A, and the OpenAI Agents SDK.
• Proven ability in AI infrastructure: production-grade inference serving, MLOps pipelines, evaluation practices, and shared services.
• Solid understanding of AI safety, alignment, privacy, and ethical development practices.
• Hands-on experience with local/open LLM runtime and serving tools (e.g., Ollama) and similar tooling for controlled deployments.
• Background in modern cloud-based, SaaS, or platform-oriented architectures, including scalable service patterns and secure API design.
• Physically located on the U.S. East Coast and willing to work effectively across multiple time zones (North America, Europe, and Asia).

Nice To Haves

• Master’s degree or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.
• Experience with agent orchestration frameworks such as Claude Subagents, AutoGen, or CrewAI.
• Expertise in prompt engineering, context engineering, RAG pipelines, and optimization.
• Expertise in deploying open-source LLMs into production (e.g., Qwen, DeepSeek, Llama, Mistral, Gemma).
• Familiarity with cloud-based AI tools (e.g., AWS Bedrock, GCP Vertex AI, Azure ML).
• Experience integrating AI capabilities into legacy web applications, desktop applications, and APIs.

Responsibilities

• Redesign and operationalize an AI-native software development lifecycle (SDLC), including: AI-assisted and AI-generated code Autonomous and semi-autonomous engineering AI agents Model-driven development and test generation AI-enabled code review, quality, and observability
• Lead AI Engineering Strategy & Execution: Define the technical roadmap, architecture standards, and delivery approach for AI-powered products and platforms—from prototype to production.
• Architect Secure, Autonomous AI Systems: Design and guide development of agent-based tools leveraging solutions like Claude Code, MCPs, A2A, Gemini CLI, the OpenAI Agents SDK, and Knowledge Graph concepts to solve complex, high-value problems.
• Develop A2A Systems: Build frameworks to enable LLMs to work together internally and externally, increasing the reach of 3E-enabled generative AI systems.
• Bridge Product & Engineering: Partner with Product, Engineering, and Customer teams to embed AI into tools that enhance usability, decision-making, and automation.
• Build Seamless API Integrations: Create scalable, secure APIs that connect AI models with web applications, internal systems, and external platforms. Integrate these with MCP for agentic use.
• Operationalize Production AI: Establish best practices for inference serving, MLOps pipelines, evaluation, observability, and shared services to ensure reliability and performance.
• Contribute to Responsible AI Practices: Stay current with AI advancements and help define responsible development standards, alignment strategies, and safety protocols.
• Build and Grow the Team: Hire, mentor, and develop a high-performing team; create a culture of accountability, transparency, and continuous improvement

Benefits

• Health, dental, and vision insurance
• Life insurance and disability coverage
• Open PTO and parental leave
• 401(k) plan with company matching
• Employee assistance program
• Voluntary supplemental benefits (Accident, Hospital Indemnity, Critical Illness)

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Number of Employees: 251-500 employees