Forward Deployed Engineer- Remote

Key Responsibilities 

Solution Design & Architecture 

• 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 

• 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 

• 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 

Collaboration & Stakeholder Engagement 

• Embed directly with product, program, and engineering teams to co-define problems and co-deliver solutions 
• Influence technical direction and build alignment across teams without relying on formal authority 
• Communicate complex technical concepts clearly to non-technical business stakeholders — in writing, in meetings, and in executive presentations 
• Mentor and elevate junior engineers, sharing patterns and practices for agentic development, prompt design, and rapid delivery 
•  Foster a collaborative, low-ego team culture where speed and quality go hand in hand