AI Platform Engineer

AI Platform EngineerHED is hiring an AI Platform Engineer to develop, evaluate, and improve the AI capabilities that support our people and our practice. About HEDWe are a team that is full of ideas, experience, creativity, passionate opinions, insatiable curiosity, uncompromising integrity, commitment, and skill. Our culture is about aspiration, embracing change and challenges, listening to (and learning from) each other, encouraging continual learning, and inspiring collective growth.

As an inclusive, integrated architecture and engineering practice, we value the diversity of perspectives, experiences, abilities, and expertise that advance both the work we do, and the world we share.

Position Summary At HED, we believe the most powerful solutions emerge when expertise, technology, and human insight come together. As a national integrated architecture and engineering firm, we are advancing how artificial intelligence connects knowledge, improves workflows, and empowers our people to deliver exceptional outcomes.

You will build and optimize production AI solutions, evaluate large language models, improve AI-generated responses, and transform organizational knowledge into secure, accessible, and actionable intelligence.

Working within our Data & AI team, you will own defined technical initiatives and collaborate with developers, data engineers, and business stakeholders.

This role offers opportunities to influence technical decisions and grow into broader platform leadership.

Essential Functions AI Model Evaluation and Performance
• Develop and maintain model benchmarking, evaluation datasets, testing methods, and performance baselines across production AI applications.
• Evaluate models, prompts, and configurations against response quality, reliability, cost, latency, and risk; document findings and recommend improvements.
• Support preproduction validation of model, prompt, and application changes.

Context Engineering and AI Optimization
• Develop and optimize retrieval-augmented generation (RAG), retrieval ranking, prompt structures, context management, and caching.
• Measure answer quality, token usage, and operating costs; use results to guide improvements.
• Collaborate with application developers to improve shared AI capabilities and user experiences.

AI Solution Development and Delivery
• Deliver defined AI use cases from requirements and design through implementation, testing, documentation, adoption, and improvement.
• Help design workflows that capture and organize employee expertise, skills, and competencies for use in AI-powered applications.
• Develop structured data models, skills taxonomies, and knowledge capture workflows; partner with data engineering to integrate governed datasets.
• Work with business stakeholders to define requirements, success criteria, and practical solutions.

Data Governance and Responsible AI
• Apply privacy, security, data classification, consent, retention, and access-control requirements to AI solutions and datasets.
• Support dataset quality, lineage, ownership, documentation, and auditability.

Technical Collaboration and Innovation
• Contribute to architecture discussions, technical reviews, coding standards, automated testing, CI/CD, and code reviews.
• Use AI-assisted development tools responsibly and share technical knowledge with colleagues.
• Evaluate emerging generative AI and agentic technologies for practical application uirements
• Approximately 4–6+ years of experience in software engineering, machine learning engineering, data engineering, or a related technical discipline.
• Hands-on experience developing, deploying, or supporting LLM applications in production.
• Experience implementing AI evaluations, benchmarks, or performance testing.
• Working…