Staff Forward Deployed Engineer
Solution Design & Architecture
Lead solution design for complex, cross-functional data and AI problems — from initial discovery through to technical blueprint.
Evaluate and select the right tools and architecture for each problem — no single stack applies across every team you support, so you must be able to reason across different platforms, data sources, and integration patterns.
Define and communicate architecture decisions, trade-offs, and delivery approaches to both technical and non-technical audiences.
Create scalable, modular systems that balance speed with enterprise standards for reliability, security, and maintainability.
Create clear technical documentation: architecture diagrams, data flow maps, API contracts, and solution briefs.
Establish reusable architecture patterns and reference designs that other engineers adopt across engagements.
AI-Assisted Solution Delivery
Use AI coding assistants as your primary development environment for day-to-day solution building — from prototyping through production implementation.
Build and maintain custom plugins/skills for your AI coding assistant that package reusable capabilities for recurring problems across teams.
Redesign and rebuild data pipelines and data flows to unblock use cases — including source integration, transformation logic, and downstream delivery.
Deploy and operate AI agents in production via AWS Bedrock AgentCore.
Translate ambiguous business requirements from stakeholders into concrete technical solutions with minimal hand-holding.
Balance speed of delivery with enterprise standards — your prototypes are production-ready, not throwaway.
Develop intuitive front-end interfaces and dashboards that bring data and AI outputs to life for business users.
AI Agent Development
Design, build, and deploy AI agents and multi-agent systems that automate complex workflows end-to-end.
Build and maintain agent skills and plugins — discrete, reusable capabilities that compose into larger agentic pipelines.
Implement and extend Model Context Protocol (MCP) servers and clients to connect agents with enterprise tools, APIs, and data sources.
Design evaluation harnesses, guardrails, and monitoring pipelines to ensure agent reliability and safety in production on AgentCore.
Stay current with the rapidly evolving agentic AI landscape (AI coding assistants, AgentCore, MCP ecosystem) and proactively bring new techniques to the practice.
Practice Leadership & Technical Strategy
Define and evolve delivery practices and playbooks used across multiple cross-functional teams.
Serve as the technical escalation point for the most ambiguous or high-stakes problems across the portfolio.
Provide direct input to the hiring manager on recurring patterns and roadmap priorities based on field signal.
Mentor and elevate other engineers on AI-assisted agentic development, plugin design, and rapid delivery.
Collaboration & Stakeholder Engagement
Embed directly with multiple cross-functional teams simultaneously 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 presentations.
Foster a collaborative, low-ego culture where speed and quality go hand in hand.