Senior Applied AI Engineer / Forward Deployed Engineer

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 pragmatic technology choices across Azure OpenAI, Azure AI Search, and open-source tools
• Document architecture, decisions, trade-offs, and operational requirements

 

Skills & Experience You Should Possess

• 5+ years of experience in software engineering, applied AI, or enterprise systems
• Strong Python development experience building production-grade APIs or services
• Hands-on experience with large language model applications
• Experience with Azure OpenAI Service, OpenAI APIs, or similar platforms
• Proven experience designing and building RAG systems
• Strong understanding of prompt design, grounding, context management, and LLM limitations
• Experience integrating with enterprise data sources, APIs, and document systems
• Ability to work directly with business stakeholders and translate needs into working solutions
• Experience working within secure, governed enterprise environments
• Strong communication, systems thinking, and problem-solving skills
• Ability to balance speed, usability, scalability, and maintainability

 

Bonus Points If You Have

• Experience in a forward-deployed, consulting, or solutions engineering role
• Hands-on experience with Azure AI Search or similar vector/hybrid search platforms
• Experience with reranking, relevance tuning, and retrieval evaluation
• Familiarity with frameworks such as LangChain, LlamaIndex, or Semantic Kernel
• Experience with LLM evaluation frameworks and quality measurement
• Background in building AI agents or workflow automation systems
• Experience with Microsoft 365, SharePoi