Overview
Location: Fully Remote (Client Team Based in Minneapolis, Minnesota) Employment Type: Full-Time
Build Practical, Production-Ready AI Solutions for the Enterprise
Trissential is hiring a Senior Applied AI Engineer / Forward Deployed Engineer to join our client’s team and help design, build, and deploy AI solutions that solve real business problems in complex enterprise environments.
This is not a research-only role. It’s an opportunity to work closely with real users, tackle ambiguous challenges, and deliver production-ready AI systems that create measurable business value. If you thrive at the intersection of engineering, data, and business impact—and enjoy turning ideas into working systems—this role is built for you.
What’s in It for You?
- Applied AI with Real Impact – Build AI-powered applications and workflows that directly improve enterprise operations and decision-making
- Forward-Deployed Engineering Experience – Work closely with stakeholders to understand workflows and deliver tailored, high-value solutions
- Ownership & Influence – Shape architecture decisions across LLM apps, RAG pipelines, APIs, integrations, and deployment strategies
- Enterprise-Grade Systems – Integrate AI with Microsoft 365, Azure, SharePoint, SQL, APIs, and large-scale enterprise platforms
- Fully Remote Flexibility – Collaborate with experienced teams while working from anywhere in the U.S.
- Production-Focused Work – Focus on reliable, scalable AI systems—not just prototypes or demos
Your Role & Responsibilities
- Partner with business and technical stakeholders to understand workflows, challenges, and success metrics
- Translate ambiguous problems into clear technical solutions, designs, and delivery plans
- Design and build AI-powered applications using LLMs, APIs, and enterprise data systems
- Develop production-grade backend services using Python and frameworks like FastAPI or Flask
- Build and maintain RAG systems, including:– Document ingestion and normalization– Chunking, metadata, and embedding strategies– Vector, keyword, and hybrid search– Reranking and relevance tuning– Source attribution and grounding
- Integrate AI solutions with SharePoint, Microsoft Graph, SQL databases, internal APIs, and business applications
- Design secure systems that respect access control, governance, and enterprise compliance requirements
- Build observable, reliable, and maintainable AI workflows in production environments
- Establish evaluation frameworks for LLM systems (accuracy, groundedness, latency, completeness, and failure modes)
- Iterate rapidly through prototypes, pilots, and production releases based on user feedback
- Collaborate with engineering, data, security, and product teams to ensure adoption and long-term sustainability
- Make pragmat