AI Forward Deployed Engineer

The Forward Deployed Engineer (FDE) is a handson, customerfacing engineering leader who bridges business intent and productiongrade AI solutions. The FDE works directly with business stakeholders, product owners, and platform teams to translate ideas into deployable solutions using an enterpriseenabled 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., 1. IdeatoProduction Solution Delivery

• Partner with business stakeholders to understand problem statements, workflows, and desired outcomes
• Convert business intent into AIenabled solution designs, agent workflows, and system architectures
• Own endtoend delivery: prototype MVP production rollout
• Deploying enterprise complex systems integrations while solving critical business problems
• Drive rapid iteration while maintaining enterprisegrade quality, security, and reliability

1. Agentic AI Solution Engineering * Design and implement agentic workflows using enterprise agentic AI platforms * Orchestrate multiagent systems that handle reasoning, planning, execution, validation, and monitoring * Encode business logic, SOPs, policies, and controls into autonomous or semiautonomous agents * Apply humanintheloop, guardrails, and fallback mechanisms where required

2. Frontier Models & Context Engineering * Work with frontier foundation models (LLMs, multimodal models) and enterpriseapproved model stacks * Perform context engineering:

• Prompt design and prompt chaining
• Tool grounding and retrievalaugmented generation (RAG)
• Knowledge graph and memory integration

Optimize solutions for accuracy, latency, cost, and reliability

1. AIFirst Engineering & Developer Tooling * Leverage AIassisted development tools to accelerate delivery:

• Cursor
• GitHub Copilot
• AIassisted testing, code review, and refactoring tools

Establish AIaugmented engineering workflows across design, build, test, and release phases

Coach teams on effective humanAI collaboration in engineering

1. Intelligent CI/CD & MLOps * Design and implement intelligent CI/CD pipelines integrating:

• AIgenerated code and test artifacts
• Policy and control validation
• Automated security and compliance checks

Integrate agentic workflows into DevSecOps / MLOps pipelines

Ensure repeatable, auditable, and scalable deployments across environments

1. Enterprise Readiness & Governance Alignment * Ensure solutions comply with:

• Security, privacy, and datahandling policies
• Model risk management and AI governance frameworks
• 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

1. Customer & Stakeholder Engagement * 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

Core Engineering & Architecture

• Strong background in software engineering (backend, APIs, distributed systems)
• Experience building productiongrade cloudnative 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, Google Cloud Platform, Azure, OpenShift)

Agentic AI & AI Engineering

• Handson 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 AIassisted testing, documentation, and code review
• Ability to design AIfirst 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

Enterprise & Soft Skills

• Strong problemsolving and analytical mindset
• Ability to work in ambiguous, fastmoving environments
• Excellent communication skills with both technical and nontechnical stakeholders
• Customercentric mindset with ownership and accountability
• Good handle on Complex enterprise system integrations, * Experience in regulated industries (banking, financial services, healthcare, etc.)
• Exposure to AI governance, model risk, and compliance frameworks
• Prior experience in customerfacing engineering roles (FDE, Solutions Engineer, Field Engineer)
• Experience contributing to platform blueprints, accelerators, or internal frameworks