Forward Deployed Engineer

Forward Deployed Engineer (FDE) - Agentic AI & Enterprise Solutions NY/ NJ/ Delaware/ Colombus/ Dallas/ Houston / FL/Chicago/ CA (Hybrid- Onsite) Contract or Fulltime Job Description ✅ Must Have Strong knowledge of AWS, Bedrock and Java is mandatory, Client operates primarily on AWS and Java, this is a key requirement.Banking domain experience is mandatory.Minimum 10+ Years experience. 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 → 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 1️⃣ Idea to Production Solution Delivery Partner with business stakeholders to understand problem statements, workflows, and desired outcomesConvert business intent into AI enabled solution designs, agent workflows, and system architecturesOwn end to end delivery: prototype → MVP → production rolloutDeploying enterprise complex systems integrations while solving critical business problemsDrive rapid iteration while maintaining enterprise grade quality, security, and reliability 2️⃣ Agentic AI Solution Engineering Design and implement agentic workflows using enterprise agentic AI platformsOrchestrate multi agent systems that handle reasoning, planning, execution, validation, and monitoringEncode business logic, SOPs, policies, and controls into autonomous or semi autonomous agentsApply human in the loop, guardrails, and fallback mechanisms where required 3️⃣ Frontier Models & Context Engineering Work with frontier foundation models (LLMs, multimodal models) and enterprise approved model stacksPerform context engineering: Prompt design and prompt chainingTool grounding and retrieval augmented generation (RAG)Knowledge graph and memory integrationOptimize solutions for accuracy, latency, cost, and reliability 4️⃣ AI First Engineering & Developer Tooling Leverage AI assisted development tools to accelerate delivery: CursorGitHub CopilotAI assisted testing, code review, and refactoring toolsEstablish AI augmented engineering workflows across design, build, test, and release phasesCoach teams on effective human AI collaboration in engineering 5️⃣ Intelligent CI/CD & MLOps Design and implement intelligent CI/CD pipelines integrating: AI generated code and test artifactsPolicy and control validationAutomated security and compliance checksIntegrate agentic workflows into DevSecOps / MLOps pipelinesEnsure repeatable, auditable, and scalable deployments across environments 6️⃣ Enterprise Readiness & Governance Alignment Ensure solutions comply with: Security, privacy, and data handling policiesModel risk management and AI governance frameworksRegulatory and audit requirements (especially in regulated industries)Collaborate with platform, security, and governance teams to operationalize guardrailsContribute patterns, blueprints, and reusable assets to the enterprise AI platform 7️⃣ Customer & Stakeholder Engagement Act as a trusted technical advisor to customers and internal stakeholdersPresent architectures, demos, and outcomes to engineering leaders, business heads, and executivesGather feedback from production usage and continuously improve solutionsServe as the "voice of the customer" back into platform and product teams ️ Required Skills & Experience Core Engineering & ArchitectureStrong background in software engineering (backend, APIs, distributed systems)Experience building production grade cloud native platforms/applicationsProficiency in at least one modern programming language (Python, Java, Go, or similar)Solid understanding of system design, scalability, and reliabilitySkilled 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 integrationUnderstanding of RAG, memory systems, and knowledge groundingSpec driven development - Architecture, Security and Application frameworks. ⚡ AI Tooling & Productivity Practical experience using Cursor, GitHub Copilot, or similar AI coding toolsFamiliarity with AI assisted testing, documentation, and code reviewAbility to design AI first developer workflows DevOps, CI/CD & Platform Integration Experience with CI/CD pipelines, infrastructure as code, and cloud platformsUnderstanding of DevSecOps and automated control enforcementFamiliarity with MLOps concepts for model lifecycle and monitoring Enterprise & Soft Skills Strong problem solving and analytical mindsetAbility to work in ambiguous, fast moving environmentsExcellent communication skills with both technical and non technical stakeholdersCustomer centric mindset with ownership and accountabilityGood 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 frameworksPrior 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 confidenceAgentic AI solutions deliver measurable business outcomesEngineering teams adopt AI first workflows with strong governanceCustomers trust the platform and the FDE as a strategic delivery partner