Forward Deployed Engineer

Job Description:

As a Forward Deployed Engineer (AI Architect), you will operate at the front lines of innovation — embedded directly with subject matter experts, product, and engineering teams to rapidly design, architect, prototype, and deploy solutions that solve high-priority business problems. This is not a traditional engineering role with long delivery cycles. You will be to go from concept to working prototype in days, not months, while maintaining enterprise-grade standards for quality, security, and scalability.

You bring an exceptional combination of skills: deep hands-on engineering experience across AI agents and full-stack development, and the interpersonal skills to earn trust, drive alignment, and influence without authority. You are equally comfortable whiteboarding a system architecture with senior stakeholders and writing production code the same afternoon. You have direct experience developing agents on platforms like AWS Agent Core, and you thrive in fast, ambiguous environments where creative thinking and execution speed matter.

Key Responsibilities:

Solution Design & Architecture

• Must have experience in a solution architect type capacity and a customer first mentality.  This is a customer facing role, so soft skills are very important.
• Lead solution design for complex, cross-functional data and AI problems — from initial discovery through to technical blueprint
• Define and communicate architecture decisions, trade-offs, and delivery approaches to both technical and non-technical audiences
• Design scalable, modular systems that balance the need for speed with enterprise standards for reliability, security, and maintainability
• Participate in architecture reviews, ensuring alignment with enterprise patterns and platform standards
• Create clear technical documentation: architecture diagrams, data flow maps, API contracts, and solution briefs

Rapid Prototyping & Solution Delivery

• Must be able to build plug ins and be able to build and scale agentic workflows into production.
• Design and deliver working prototypes for complex data and AI problems within compressed timeframes, often days to weeks
• Translate ambiguous business requirements into concrete technical solutions with minimal hand-holding
• Balance speed of delivery with enterprise standards — your prototypes are production-ready, not throwaway
• Continuously iterate on solutions based on direct feedback from product managers, program leads, and end users
• Develop intuitive front-end interfaces and dashboards that bring data and AI outputs to life for business users
• Apply strong UX instincts to simplify complex flows and make agent outputs accessible and actionable for non-technical stakeholders

AI Agent Development

• Experience deploying AgentCore Bedrock is highly preferred, but other cloud technologies are acceptable if they are able to deploy agents within AgentCore.
• Design, build, and deploy AI agents and multi-agent systems that automate complex workflows end-to-end
• Develop and maintain agent skills — discrete, reusable capabilities that compose into larger agentic pipelines
• Implement and extend Model Context Protocol (MCP) servers and clients to connect AI agents with enterprise tools, APIs, and data sources
• Design evaluation harnesses, guardrails, and monitoring pipelines to ensure agent reliability and safety in production
• Stay current with the rapidly evolving agentic AI landscape and proactively introduce new techniques and tooling to the team
• Integrate LLMs, RAG systems, and ML models into production workflows

Regards,

GAURAV M DUBEY

Technical Lead - Talent Acquisition

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P: +1 , Extn # 341

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