AI Engineer
About The Position
In this role, you’ll lead the design, build, and run of agentic AI solutions that change how a complex, enterprise-grade business operates. This role operates as part of Mattamy’s enterprise AI team, working closely with AI product leadership and platform teams as the AI capability scales. You’ll own the technical architecture for assigned AI solutions across RAG pipelines, LLM configuration, system integrations, and data flows, and you’ll contribute to the technical standards and reference patterns across internal and partner-led builds. This is an ideal opportunity for a senior AI engineer who wants end-to-end ownership — solution design through production run — and the chance to shape an AI program as it scales.
Requirements
- 5+ years of software engineering experience, including 2+ years building production AI/LLM solutions, or an equivalent combination of education and experience
- Hands-on experience building on Azure AI Foundry (or equivalent) with OpenAI / Azure OpenAI and Anthropic Claude — prompt design, tool/function calling, structured outputs, and managing cost, latency, and token limits
- Proven experience designing and shipping RAG pipelines — chunking, embeddings, vector stores, hybrid retrieval, re-ranking, and grounding strategies that hold up in production
- Experience leading agent architecture — orchestration, tool use, multi-step reasoning, memory, and integration with enterprise systems and data sources
- Strong software engineering fundamentals — Python or TypeScript, APIs, version control (Git), CI/CD, and Agile delivery tools (e.g., Azure DevOps)
- Experience running AI solutions in production — evaluation frameworks, observability, regression testing, and tuning for accuracy, latency, and cost
- Working knowledge of responsible AI — data privacy and PII handling, access controls, prompt and output safety, bias and hallucination mitigation, and human-in-the-loop design
- Experience leading external delivery partners or vendor teams — setting technical direction, reviewing work, and signing off on quality, plus strong written and verbal communication with technical and non-technical audiences
Responsibilities
- Lead the architecture and design of agentic AI solutions, including RAG pipelines, LLM configuration, prompt and tool design, system integrations, and end-to-end data flows
- Own technical quality and engineering standards across all AI builds, in alignment with the enterprise AI architecture and governance framework— code review, design review, evaluation criteria, and production readiness
- Write production-grade code as a hands-on contributor — prototype quickly, ship working solutions end-to-end, and stay close to the implementation details to make AI systems reliable
- Build and maintain core AI components hands-on — retrieval pipelines, agent orchestration, and integrations with enterprise systems and data sources
- Own production run of deployed AI solutions — observability, evaluations, incident response, and ongoing tuning for accuracy, latency, cost, and drift
- Establish and maintain architecture documentation, reference patterns, and runbooks so the program can scale across multiple concurrent builds
- Embed responsible AI practices into every build — data privacy, access controls, prompt and output safety, evaluation, and human-in-the-loop where it matters
- Partner with business, data, and platform teams to translate prioritized AI use cases into production-ready AI solutions that deliver measurable outcomes
Benefits
- annual bonus program
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
