Director, Applied AI Engineering

About 3E

We are a mission-driven company dedicated to creating a safer and more sustainable world!

3E provides award-winning regulatory expertise and cutting-edge technology that seamlessly integrates data and intelligence regarding chemicals, regulations, products, and supply chains for over 5,000 customers globally.

With more than 35 years of experience and 15 locations across North America, Europe, and Asia, we are connecting our customers to a new class of expert-led AI solutions, specifically designed to accelerate future product compliance with trust, speed, and domain authority.

Are you ready to help shape the future? Come join us!

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 leadership 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, AI amplifies human capability at scale, and leave a lasting imprint on both 3E and the broader industry.

This position supports remote work and should be based near one of our U.S. East Coast office locations:
Bethesda, MD, or Canton, OH.

• 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

• Minimum Qualifications
• Bachelor’s degree in Computer Science, Data Science, Machine Learning, or a related field, or equivalent experience building and shipping production-grade AI systems and or SaaS platforms at scale
• Demonstrated success leading engineering organizations through meaningful transformation, with measurable improvements in speed, quality, reliability, and leverage
• Proven experience re-architecting software development life cycles and engineering workflows to AI-native or…