Forward Deployed Engineer; FDE; Agentic AI & Enterprise Solutions
Job in
Town of Texas, Marathon County, Wisconsin, USA
Listed on 2026-10-14
Listing for:
Talentola
Full Time
position Listed on 2026-10-14
Job specializations:
-
Software Development
AI Engineer (Applied/Software), DevOps, Software Architect
Job Description & How to Apply Below
Location: Town of Texas
The Forward Deployed Engineer (FDE) is a hands on, customer facing engineering leader who bridges business intent and production grade AI solutions. The FDE works directly with business stakeholders, product owners, and platform teams to translate ideas into deployable solutions using an enterprise enabled agentic AI platform and a governed adoption framework.
This role blends solution engineering, AI engineering, and delivery leadership, with strong ownership from problem discovery ? architecture ? build ? deployment ? optimization. The FDE operates close to customers and internal product teams, ensuring solutions deliver measurable business outcomes while meeting enterprise, security, and compliance standards.
Key Responsibilities 1. Idea to Production Solution Delivery- " Partner with business stakeholders to understand problem statements, workflows, and desired outcomes
- " Convert business intent into AI enabled solution designs, agent workflows, and system architectures
- " Own end to end delivery: prototype ? MVP ? production rollout
- " Deploying enterprise complex systems integrations while solving critical business problems
- " Drive rapid iteration while maintaining enterprise grade quality, security, and reliability
- " Design and implement agentic workflows using enterprise agentic AI platforms
- " Orchestrate multi agent systems that handle reasoning, planning, execution, validation, and monitoring
- " Encode business logic, SOPs, policies, and controls into autonomous or semi autonomous agents
- " Apply human in the loop, guardrails, and fallback mechanisms where required
- " Work with frontier foundation models (LLMs, multimodal models) and enterprise approved model stacks
- o Prompt design and prompt chaining
- o Tool grounding and retrieval augmented generation (RAG)
- o Knowledge graph and memory integration
- " Optimize solutions for accuracy, latency, cost, and reliability
- " Leverage AI assisted development tools to accelerate delivery:
- o Cursor
- o AI assisted testing, code review, and refactoring tools
- " Establish AI augmented engineering workflows across design, build, test, and release phases
- " Coach teams on effective human AI collaboration in engineering
- " Design and implement intelligent CI/CD pipelines integrating:
- o AI generated code and test artifacts
- o Policy and control validation
- o Automated security and compliance checks
- " Integrate agentic workflows into Dev Sec Ops / MLOps pipelines
- " Ensure repeatable, auditable, and scalable deployments across environments
- " Ensure solutions comply with:
- o Security, privacy, and data handling policies
- o Model risk management and AI governance frameworks
- o Regulatory and audit requirements (especially in regulated industries)
- " Collaborate with platform, security, and governance teams to operationalize guardrails
- " Contribute patterns, blueprints, and reusable assets to the enterprise AI platform
- " Act as a trusted technical advisor to customers and internal stakeholders
- " Present architectures, demos, and outcomes to engineering leaders, business heads, and executives
- " Gather feedback from production usage and continuously improve solutions
- " Serve as the "voice of the customer" back into platform and product teams
- " Strong background in software engineering (backend, APIs, distributed systems)
- " Experience building production grade cloud native platforms/applications
- " Proficiency in at least one modern programming language (Python, Java, Go, or similar)
- " Solid understanding of system design, scalability, and reliability
- " Skilled in hyperscale platforms (AWS, GCP, Azure, Open Shift)
- " Hands on experience with agentic AI frameworks and orchestration patterns (n8n, Lang Graph, Semantic Kernel, CrewAI, etc.)
- " Experience working with LLMs / foundation models in enterprise settings (Claude, Gemini, OpenAI)
- " Strong skills in prompt engineering, context engineering, and tool integration
- " Understanding of RAG, memory systems, and knowledge grounding
- " Spec driven development - Architecture, Security and Application frameworks.
- " Practical experience using Cursor, Git Hub Copilot, or similar AI coding tools
- " Familiarity with AI assisted testing, documentation, and code review
- " Ability to design AI first developer workflows
- " Experience with CI/CD…
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