Sr. Software Development Engineer, AWS Forward Deployed Engineering

Description We’re looking for a Senior Software Development Engineer who wants to build AI-powered products that change how enterprises move to the cloud — and who thrives as the technical anchor of an AWS 2-pizza team.

You’ll own the architecture and delivery of production systems that power how AWS delivers enterprise cloud migrations and modernization at scale. Our team builds agentic AI solutions — platforms where AI agents and human consultants collaborate as a unified delivery team — reducing migration timelines from years to months and cutting costs dramatically. The work spans the full migration lifecycle: assessment, planning, orchestration, execution, and integration with AWS Transform (Amazon’s agentic AI service for enterprise modernization). You’ll be building real software used daily by thousands of practitioners serving Fortune 500 customers.

This is a hands-on builder role with leadership expectations. You’ll write code, design systems, lead projects across multiple engineers, mentor teammates, and own operational excellence for your services — all within a product engineering org that ships fast and measures success by adoption and customer outcomes.

What We Build

Our platform is a multi-agent system that orchestrates enterprise cloud migrations end-to-end. Our business spans several domains:

• Agentic AI — AI agents that autonomously handle migration tasks (discovery, wave planning, runbook generation, infrastructure provisioning) while coordinating with human consultants
• Orchestration and workflow — the coordination layer that enables multiple agents and humans to work in parallel with shared context and minimal overhead
• Platform infrastructure — shared services (project datastores, external system connectors, agent lifecycle management) that underpin the PCAM ecosystem
• AWS Transform integration — bidirectional data and workflow connectivity with AWS’s flagship enterprise modernization service
• Extensibility — frameworks that enable ProServe teams to build and deploy custom agents for specialized customer needs

All of it involves building agentic AI systems at production scale with real users and real constraints.

Why This Team

• You’ll build, not consult — we’re a product engineering org inside Professional Services. We own our roadmap, ship on our cadence, and maintain our services. This is not billable-hours consulting.
• AI-native problems — every team is working on some aspect of agentic AI: building agents, orchestrating them, evaluating their outputs, or making them extensible. You’ll be at the frontier of applied AI engineering.
• Small team, big impact — as an AWS 2-pizza team, you’ll have direct ownership of significant components. Your architecture decisions directly impact 5000+ consultants across 60+ countries delivering $1B+ in active delivery pipeline.
• Full-stack ownership — from React frontends to CDK infrastructure to AI agent logic. No artificial boundaries between “frontend” and “backend” engineers.
• Career growth — we invest in developing senior engineers toward Principal levels. You’ll work alongside senior architects and receive direct mentorship on expanding your technical influence beyond a single team.
• Direct customer engagement — you’ll occasionally engage directly on customer migrations, seeing your tools in action and bringing insights back to improve the platform.

Key job responsibilities

• Own team-level architecture — design systems that are simple, extensible, and operationally sound
• Influence design and technical decisions beyond your immediate team, contributing to org-wide architectural direction and engineering standards
• Lead projects spanning multiple engineers; make sound technical decisions and drive execution from design through production deployment
• Design and build agentic AI components — whether that’s agent logic, orchestration workflows, evaluation pipelines, or integration APIs
• Write production code daily — you should spend the majority of your time building, not meeting
• Set engineering standards on your team: code quality, testing practices, CI/CD pipelines, observability, and incident response
• Solve complex distributed systems problems where trade-offs between latency, consistency, extensibility, and cost aren’t obvious
• Proactively identify and resolve technical debt; simplify systems rather than layering complexity
• Mentor and grow engineers on your team; help juni…