Director, Principal AI Engineer

Role Summary

Lead a small, cross-functional AI Accelerator pod to design and deliver generative AI solutions across Commercialization, R&D, Manufacturing, and Enabling Functions. Act as player-coach, spending roughly 60% of your time hands-on in technical architecture, system and solution design, and building cloud-native GenAI applications, and 40% leading and developing your team. You will own one to two 12-week Accelerator projects at a time, shaping project charters, guiding technical decisions, and delivering AI-powered solutions using modern LLM, ML, and Cloud services and coding agents. Partnering closely with business, product, and technology stakeholders, you will establish reusable patterns, promote responsible AI practices, and help transition successful proofs of concept for scale into impactful, enterprise-wide solutions.

Responsibilities

• Own end-to-end delivery of 12-week AI Accelerator projects, from problem framing and solution design through experimentation and handover.
• Shape use cases, scope, and success metrics in collaboration with business stakeholders, product owners, and the AI Accelerator Hub.
• Manage trade-offs between experimentation and robustness to keep projects on track and outcome-focused.
• Ensure smooth transition of successful POCs into Scale phase with functional IT and business teams.
• Lead a small, multi-disciplinary pod of frontend engineers, application/cloud engineers, data scientists, and data engineers.
• Provide coaching, feedback, and technical mentoring to grow skills and foster a high-performing, inclusive culture.
• Partner with talent acquisition to hire and onboard new team members; onboard and manage staff-augmentation resources, if needed.
• Establish lightweight, effective ways of working aligned with agile delivery and rapid experimentation.
• Act as technical lead and architect for GenAI solutions, driving technical architecture, system design, and solution design for LLM-based applications and agentic systems.
• Design and implement solutions involving, but not limited to, context engineering, MCP servers, structured and unstructured data retrieval and manipulation, vector search, and multi-modal inputs (text, tables, images).
• Build and orchestrate agents and tools to integrate enterprise systems and workflows.
• Use coding agents effectively (e.g., Claude Code, Codex/GitHub Copilot-style tools, Gemini CLI) to accelerate development while maintaining quality.
• Partner with stakeholders across Commercialization, R&D, Manufacturing, and Enabling Functions.
• Communicate progress, risks, and outcomes clearly to both technical teams and senior leadership.
• Contribute to shared patterns, templates, and components for future accelerator projects.
• Embed responsible AI practices, including basic safety, evaluation, and guardrail considerations in GenAI solutions.

Qualifications

• Bachelor's degree in Engineering, Science, Business, or a related field.
• 7+ years of experience in software engineering, data science, or related technology roles with increasing responsibility.
• Proven track record designing and delivering GenAI and traditional software applications.
• Deep expertise in Python; experience with TypeScript and modern frontend development (e.g., React).
• Strong experience with MCP, context engineering, multi-modal GenAI inputs, and vector databases.
• Hands-on experience with AWS; familiarity with Azure and/or GCP is a plus.
• Practical experience with Azure OpenAI and AWS Bedrock.
• Effective use of coding agents (e.g., Claude Code, Codex, Gemini CLI).
• Comfort with GitHub and DevOps practices.
• Experience with Databricks, Terraform/CloudFormation, MLOps, or app observability is a plus.
• Knowledge of and experience in agile ways of working.
• Demonstrated people-management experience leading small engineering/data teams.
• Excellent written and verbal communication skills across technical and executive audiences.