Forward Deployed Engineer

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

Client location (NY/ NJ/ Delaware/ Colombus/ Plano/ Houston / Chicago) - 2-3 Days Onsite

Domain: Banking/finance

Experience: Minimum 10+ years of experience.

Must Have : Strong knowledge of AWS, Bedrock and Java is mandatory. The client operates primarily on AWS and Java, making this a key requirement.

Banking domain experience is mandatory.

Role Overview

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 to architecture, build, deployment, and 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

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 from prototype to MVP to production rollout.
• Deploy complex enterprise system integrations while solving critical business problems.
• Drive rapid iteration while maintaining enterprise-grade quality, security, and reliability.

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.

Frontier Models and Context Engineering

• Work with frontier foundation models, including LLMs and multimodal models, and enterprise-approved model stacks.
• Perform context engineering, including prompt design and prompt chaining, tool grounding and retrieval-augmented generation (RAG), and knowledge graph and memory integration.
• Optimize solutions for accuracy, latency, cost, and reliability.

AI-First Engineering and Developer Tooling

• Leverage AI-assisted development tools to accelerate delivery, including Cursor, GitHub Copilot, and 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.

Intelligent CI/CD and MLOps

• Design and implement intelligent CI/CD pipelines integrating AI-generated code and test artifacts, policy and control validation, and automated security and compliance checks.
• Integrate agentic workflows into DevSecOps and MLOps pipelines.
• Ensure repeatable, auditable, and scalable deployments across environments.

Enterprise Readiness and Governance Alignment

• Ensure solutions comply with security, privacy, and data handling policies, model risk management and AI governance frameworks, and 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

Customer and 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 to platform and product teams.

Required Skills and Experience

• Core Engineering and Architecture
• Strong background in software engineering, including backend development, APIs, and distributed systems.
• Experience building production-grade cloud-native platforms and applications.
• Proficiency in at least one modern programming language, such as Python, Java, or Go.
• Solid understanding of system design, scalability, and reliability.
• Experience with hyperscale platforms such as AWS, GCP, Azure, or OpenShift.
• Agentic AI and AI Engineering
• Hands-on experience with agentic AI frameworks and orchestration patterns such as n8n, LangGraph, Semantic Kernel, and CrewAI.
• Experience working with LLMs and foundation models in enterprise settings, including Claude, Gemini, and OpenAI.
• Strong skills in prompt engineering, context engineering, and tool integration.
• Understanding of RAG, memory systems, and knowledge grounding.
• Spec-driven development covering architecture, security, and application frameworks.
• AI Tooling and 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, and 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 and Soft Skills
• 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 understanding of complex enterprise system integrations.

Preferred Qualifications

• Experience in regulated industries such as banking, financial services, or healthcare.
• Exposure to AI governance, model risk, and compliance frameworks.
• Prior experience in customer-facing engineering roles such as Forward Deployed Engineer, Solutions Engineer, or Field Engineer.
• Experience contributing to platform blueprints, accelerators, or internal frameworks.