Staff Forward Deployed Engineer

Role OverviewAs a Staff Forward Deployed Engineer, you will operate at the front lines of innovation — embedded directly with multiple cross-functional teams to rapidly design, architect, prototype, and deploy solutions that solve their highest-priority problems. This is not a traditional engineering role with long delivery cycles: you will be expected to go from concept to working prototype in days, not months, while maintaining enterprise-grade standards for quality, security, and scalability.You will act as the embedded technical owner across several teams simultaneously — diagnosing their workflow and data problems, then architecting and building the fix yourself. You will use modern AI coding assistants day-to-day to design and implement solutions, and you're expected to be fluent extending that toolset — building custom plugins/skills, redesigning data pipelines and data flows, and deploying agents to production via AWS Bedrock AgentCore. At the Staff level, your impact extends beyond any single team: you define the patterns and playbooks other engineers use to deliver, and you act as the escalation point for the hardest technical and stakeholder problems across the portfolio.You bring an exceptional combination of skills: deep hands-on engineering experience across AI agents, data architecture, and full-stack development, and the interpersonal skills to earn trust, drive alignment, and influence without authority across multiple teams at once. You are equally comfortable whiteboarding a system architecture with senior stakeholders and shipping production code the same afternoon.Key ResponsibilitiesSolution Design & ArchitectureLead solution design for complex, cross-functional data and AI problems — from initial discovery through to technical blueprintEvaluate 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 patternsDefine and communicate architecture decisions, trade-offs, and delivery approaches to both technical and non-technical audiencesDesign scalable, modular systems that balance speed with enterprise standards for reliability, security, and maintainabilityCreate clear technical documentation: architecture diagrams, data flow maps, API contracts, and solution briefsEstablish reusable architecture patterns and reference designs that other engineers adopt across engagementsAI-Assisted Solution DeliveryUse AI coding assistants as your primary development environment for day-to-day solution building — from prototyping through production implementationBuild and maintain custom plugins/skills for your AI coding assistant that package reusable capabilities for recurring problems across teamsRedesign and rebuild data pipelines and data flows to unblock use cases — including source integration, transformation logic, and downstream deliveryDeploy and operate AI agents in production via AWS Bedrock AgentCoreTranslate ambiguous business requirements from stakeholders into concrete technical solutions with minimal hand-holdingBalance speed of delivery with enterprise standards — your prototypes are production-ready, not throwawayDevelop intuitive front-end interfaces and dashboards that bring data and AI outputs to life for business usersAI Agent DevelopmentDesign, build, and deploy AI agents and multi-agent systems that automate complex workflows end-to-endDevelop and maintain agent skills and plugins — discrete, reusable capabilities that compose into larger agentic pipelinesImplement and extend Model Context Protocol (MCP) servers and clients to connect agents with enterprise tools, APIs, and data sourcesDesign evaluation harnesses, guardrails, and monitoring pipelines to ensure agent reliability and safety in production on AgentCoreStay current with the rapidly evolving agentic AI landscape (AI coding assistants, AgentCore, MCP ecosystem) and proactively bring new techniques to the practicePractice Leadership & Technical StrategyDefine and evolve delivery practices and playbooks used across multiple cross-functional teamsServe as the technical escalation point for the most ambiguous or high-stakes problems across the portfolioProvide direct input to the hiring manager on recurring patterns and roadmap priorities based on field signalMentor and elevate other engineers on AI-assisted agentic development, plugin design, and rapid deliveryCollaboration & Stakeholder EngagementEmbed directly with multiple cross-functional teams simultaneously to co-define problems and co-deliver solutionsInfluence technical direction and build alignment across teams without relying on formal authorityCommunicate complex technical concepts clearly to non-technical business stakeholders — in writing, in meetings, and in presentationsFoster a collaborative, low-ego culture where speed and quality go hand in handQualificationsRequired:8–12+ years of software engineering experience, with substantial time in customer-facing or embedded technical delivery rolesStrong software architecture background — able to independently design and defend system architecture across varied tools and platforms, not tied to one stackDirect hands-on experience using AI coding assistants (e.g., Claude, Cursor, GitHub Copilot) as a primary development workflow; experience building custom plugins/skills for these tools is a strong plusDirect, hands-on experience building and deploying AI agents on AWS Bedrock AgentCore — requiredExperience with Model Context Protocol (MCP) server/client implementation — requiredData engineering experience — building and redesigning data pipelines and data flows across varied sourcesFull-stack development proficiency — backend services, APIs, and front-end interfaces/dashboardsDemonstrated experience mentoring engineers and defining technical standards adopted beyond your own workExcellent written and verbal communication skills; able to manage multiple concurrent internal stakeholder relationships