Sr AI Engineer

Job title: Sr. AI Engineer

Department / Division: Artificial Intelligence / Technology

Salary Range: $115,419/yr - $142,576/yr plus bonus

Location: Ada, MI (Onsite)

What we’re looking for

We’re looking for an experienced AI Engineer to help design, build, and operate production-grade AI capabilities that are reused across the enterprise. This role sits at the intersection of hands-on engineering, platform thinking, and cross-team enablement.

You’ll work on agentic systems, retrieval-augmented generation (RAG) pipelines, and reusable AI services that power real business use cases. Depending on experience, this role may focus on owning individual AI capabilities end-to-end or setting technical direction across multiple solutions and teams.

What you’ll do day to day:

• Design, build, and operate production AI systems including agentic workflows, RAG pipelines, and LLM-powered services
• Partner with product managers and business stakeholders to translate ambiguous problems into well-scoped, feasible AI solutions
• Implement multi-agent architectures with memory, state management, tool orchestration, and guardrails
• Build and tune RAG systems (chunking strategies, embeddings, vector stores, hybrid search, reranking, citation grounding)
• Develop evaluation frameworks to measure quality, safety, latency, and cost using automated and human-in-the-loop approaches
• Implement observability, monitoring, and incident response practices for AI systems in production
• Contribute to shared AI platform standards, reference architectures, and reusable components
• Support and enable other engineering teams through design reviews, pairing, documentation, and pattern libraries

For more experienced candidates, this role may also include defining reference architectures, influencing platform standards, mentoring multiple engineers, and guiding build-vs-buy decisions across teams.

Required Qualifications

• At least 6 years experience in Software Development or AI Engineering
• Hands-on experience building and operating production LLM-powered applications
• Experience with retrieval-augmented generation (RAG), including embeddings, vector stores, and grounding strategies
• Experience designing agentic or multi-step AI systems with tool use, orchestration, and state management
• Proficiency in Python; working knowledge of JavaScript/TypeScript and SQL
• Experience working in at least one major cloud AI platform (AWS, GCP, or Azure)
• Strong software engineering fundamentals: testing, code review, CI/CD, version control, and documentation
• Experience implementing monitoring, logging, and evaluation for AI systems in production
Ability to communicate technical trade-offs clearly to both technical and non-technical partners

Skills to Be Successful in the Role

• Structured prompt engineering and prompt lifecycle management
• Evaluation and LLMOps practices (quality measurement, drift detection, rollback strategies)
• Systems thinking and comfort operating AI services at scale
• Strong collaboration and influence skills across engineering and business teams
• Clear technical writing (design docs, architecture diagrams, post-incident reviews)
Curiosity and sound judgment when assessing new tools, frameworks, and vendors

What’s Special About This Team

This team builds shared AI capabilities that other teams across the organization rely on. Instead of one-off solutions, the focus is on creating secure, scalable, and reusable AI foundations that accelerate adoption across domains.

Engineers on this team work closely with product, platform, security, and functional technology partners. The environment balances hands-on building with long-term platform thinking, and the team plays a key role in shaping how AI is responsibly deployed at enterprise scale.