Forward Deployed Engineer / Agentic AI Claude Engineer /Architect

Job Summary We are seeking a Forward Deployed Engineer (FDE) to support an agentic AI project. The role combines hands-on AI agent development, solution architecture, rapid prototyping, and customer-facing technical leadership. The ideal candidate will work directly with subject matter experts, product, and engineering teams to rapidly design, architect, prototype, and deploy solutions that address high-priority business problems. This role requires the ability to move from concept to working prototype in days or weeks while maintaining enterprise standards for security, scalability, reliability, and maintainability. Key Responsibilities Lead solution design for complex, cross-functional data and AI problems from initial discovery through technical blueprint. Define and communicate architecture decisions, trade-offs, and delivery approaches to technical and non-technical audiences. Design scalable and modular systems that balance rapid delivery with enterprise standards for reliability, security, and maintainability. Participate in architecture reviews and ensure alignment with enterprise patterns and platform standards. Create technical documentation including architecture diagrams, data flow maps, API contracts, and solution briefs. Design and deliver working prototypes for complex data and AI problems within compressed timeframes. Translate ambiguous business requirements into concrete technical solutions with minimal hand-holding. Continuously iterate on solutions based on feedback from product managers, program leads, and end users. Design, build, and deploy AI agents and multi-agent systems that automate complex workflows end-to-end. Develop and maintain reusable agent skills and capabilities that can be composed 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. Integrate LLMs, RAG systems, and ML models into production workflows. Collaborate directly with product, program, and engineering teams to define problems and 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. Mentor junior engineers and share best practices for agentic development, prompt design, and rapid delivery. Required Qualifications Hands-on experience developing agentic AI workflows is mandatory. Strong hands-on experience developing AI agents using Claude. Experience building and maintaining plugins, agent skills, and reusable capabilities. Experience with agentic AI frameworks, orchestration, tool use, and multi-agent systems. Experience with Model Context Protocol (MCP), including MCP servers and clients. Demonstrated ability to rapidly prototype and deploy AI solutions into production. Cloud experience with at least one major cloud provider. Experience deploying and scaling AI solutions in cloud environments. Strong software engineering and full-stack development experience. Experience designing scalable, modular, secure, and maintainable enterprise solutions. Strong solution architecture and technical design capabilities. Experience with LLMs, RAG systems, prompt engineering, evaluation, guardrails, and AI/ML integrations. Ability to translate ambiguous business requirements into practical technical solutions. Strong customer-facing and stakeholder communication skills. Ability to work independently, take ownership, and lead without formal authority. Preferred Qualifications Experience with AWS Agent Core and Amazon Bedrock. Equivalent AI/cloud deployment experience with Microsoft Azure or Google Cloud Platform. Experience with Claude and Anthropic tooling. Experience building multi-agent systems. Experience developing MCP-based enterprise integrations. Experience with AI evaluation frameworks, guardrails, and observability. Experience developing front-end applications, dashboards, or user interfaces for AI solutions. Experience working directly with enterprise customers and business stakeholders. Education: Bachelors Degree