Forward Deployed Engineer (FDE) - Agentic AI & Enterprise Solutions

Talentola; Town of Texas (WI); On-site; USD 140,000 - 195,000; Full time

Job summary

Talentola seeks a Forward Deployed Engineer to lead customer-facing AI deployments. You will translate business needs into production-grade AI solutions, partnering with stakeholders, product teams, and platform engineers to drive measurable outcomes.

This role blends solution engineering, AI engineering, and delivery leadership, with ownership from discovery through deployment and governance. You will design agentic workflows and help teams adopt AI-first practices at scale.

Qualifications

• Strong background in software engineering (backend, APIs, distributed systems).
• Experience building production-grade cloud-native platforms/apps.
• Proficiency in at least one modern programming language (Python, Java, Go).
• Solid understanding of system design, scalability, and reliability.
• Skilled in hyperscale platforms (AWS, GCP, Azure, OpenShift).

Responsibilities

• Idea to Production Solution Delivery: partner with stakeholders to understand problems and deliver end-to-end AI-enabled solutions.
• Agentic AI & AI Engineering: design and orchestrate agentic workflows and multi-agent systems with governance.
• AI First Engineering & Developer Tooling: leverage AI tooling to accelerate delivery and establish AI-driven workflows across SDLC.
• Enterprise Readiness & Governance Alignment: ensure security, privacy, data handling, and governance alignment with enterprise standards.

Skills

Software engineering

Production grade cloud-native

Modern programming language

System design & scale

Cloud platforms

Tools

Cursor

LangGraph

Semantic Kernel

CrewAI

Job description

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

2. Agentic AI Solution Engineering

• " 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

4. AI First Engineering & Developer Tooling

• " 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 DevSecOps / MLOps pipelines
• " Ensure repeatable, auditable, and scalable deployments across environments

6. Enterprise Readiness & Governance Alignment

• " 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

Required Skills & Experience

Core Engineering & Architecture

• " 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, OpenShift)

Agentic AI & AI Engineering

• " Hands on experience with agentic AI frameworks and orchestration patterns (n8n, LangGraph, 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.

AI Tooling & Productivity

• " Practical experience using Cursor, GitHub Copilot, or similar AI coding tools
• " Familiarity with AI assisted testing, documentation, and code review
• " Ability to design AI first developer workflows

DevOps, CI/CD & Platform Integration

• " Experience with CI/CD pipelines, infrastructure as code, and cloud platforms
• " Understanding of DevSecOps and automated control enforcement
• " Familiarity with MLOps concepts for model lifecycle and monitoring
• " Strong problem solving and analytical mindset
• " Ability to work in ambiguous, fast moving environments
• " Excellent communication skills with both technical and non technical stakeholders
• " Customer centric mindset with ownership and accountability
• " Good handle on Complex enterprise system integrations

Preferred Qualifications

• " Experience in regulated industries (banking, financial services, healthcare, etc.)
• " Exposure to AI governance, model risk, and compliance frameworks
• " Prior experience in customer facing engineering roles (FDE, Solutions Engineer, Field Engineer)
• " Experience contributing to platform blueprints, accelerators, or internal frameworks

What Success Looks Like

• " Business ideas move to production faster and with higher confidence
• " Agentic AI solutions deliver measurable business outcomes
• " Engineering teams adopt AI first workflows with strong governance
• " Customers trust the platform and the FDE as a strategic delivery partner