Forward Deployed Engineer - Implementation Technical Lead

Proactive Technology Management•Detroit, MI

7d•Hybrid

About The Position

You are an embedded builder who bridges frontier AI products and production-grade reality inside our clients' operations. After our Fusion Discovery practice ships the prioritized roadmap, you are the named technical principal who turns that roadmap into running software — code, deploy, integrate, ship — inside the client's Azure subscription, against their data, under their compliance constraints, on the calendar they signed up for. You are the FDE in the literal sense the term means in 2026: an embedded operator with a founder's mindset who owns outcomes end to end. Discovery hands you a scoped milestone roadmap and a Statement of Work. You take it from there. You can expect to travel up to 30% of the time with this position. The FDE market is hot in 2026 and the role definition varies wildly across companies. PTM's flavor is specific, and we are explicit about it. You will: write production code that ships into the client's runtime. Build agentic systems with PydanticAI. Stand up event-driven ETL on Azure Container App Jobs. Scaffold lovable.dev → Static Web App frontends backed by FastAPI or ASP.NET Core BFFs (Backends-for-Frontends). Provision the whole stack with Bicep + azd. Wire structured logging, LLM cost telemetry, and the auth gateway from commit #1. Own the engagement's technical outcome. You will not: run discovery interviews, facilitate executive prioritization workshops, or produce the Solution Architecture Document. Our Fusion Discovery practice does that upstream and hands you their output. You may sit in on the final readout to take ownership of the implementation phase. The customer-facing volume sits with Discovery. You carry the technical volume. If you came into the FDE category because you want to be the engineer who actually ships the system the slideware promised — at a firm where validators are written before production code, every interface gets a documented contract, and the first commit boots a working full local stack — this is the role. In your first twelve months, you will serve as the technical lead on three to five Fusion Development engagements. Each one ships: A working production deployment in the client's Azure subscription, deployed via azd up and reproducible on demand. Vertical slices of demonstrable client value delivered against the milestone roadmap from Discovery. At least one KPI moved, with structured telemetry to prove it. A clean handoff document for ongoing operations: runbooks, infrastructure contracts, and the digital twin of the decisions made along the way.

Requirements

Seven or more years of production software engineering experience, with at least three at senior-IC or tech-lead level.
Deep Python: typed code, async, packaging via uv, FastAPI, Pydantic. PydanticAI or comparable agentic-systems experience is a strong plus.
Working competence in TypeScript + React. You do not need to be a frontend specialist; you do need to be able to wire a lovable.dev scaffold into your BFF without help.
Azure production experience: Container Apps, Functions, Static Web Apps, Azure SQL, Key Vault, Bicep + azd. Equivalent depth in another cloud is acceptable if you are willing to convert quickly.
Observability fluency: structured logging, distributed tracing, OTEL, log-trace correlation. You have shipped a service where you knew what was happening in production because you instrumented it that way.
Test discipline: you have written tests before production code on purpose, and you can explain why. pytest + property-based testing experience preferred.
Comfort with client-facing technical work: architecture standups, escalations, demo days. You do not need to be a presenter; you do need to be able to defend a technical decision in a room that includes the client's CTO.
US work authorization.

Nice To Haves

ASP.NET Core / C# production experience.
Healthcare engagement experience, particularly in HIPAA-aware system design, EHR integration, FHIR / HL7, claims data, or revenue-cycle-adjacent systems. The first twelve months of engagements are healthcare-weighted.
Experience with dotenvx, SOPS, or comparable encrypted-configuration workflows.
Experience with .NET Aspire AppHost or a comparable multi-service local orchestration tool.
Prior FDE, solutions-architect, or embedded-consultant experience at a vendor or services firm.

Responsibilities

Convert the Discovery roadmap into an executable engineering plan with swimlanes, interface contracts, and validator-first todos.
Scaffold the first commit as a working local full stack — frontend, backend, database, auth gateway, observability, IaC (Infrastructure as Code) — bootable with one command on a fresh clone. We do not believe in scaffold-then-wire-later.
Implement Python services (FastAPI BFFs, event-driven ETL on Azure Container App Jobs, PydanticAI agentic systems) under our RPIR validator-first loop: Research, Plan, Implement validators RED, implement production code GREEN, Review.
Build ASP.NET Core BFFs when the client's existing investment or team strength calls for it. Use .NET Aspire AppHost for local orchestration when there are three or more services or any polyglot mix.
Wire frontends scaffolded via lovable.dev into your BFF, hosted on Azure Static Web Apps.
Stand up the Azure footprint with Bicep + azd: subscription-level deployments, module contracts, mandatory tagging, Key Vault-backed configuration, and what-if gates on every pull request.
Instrument structured logging from commit #1 (structlog with callsite metadata), wire OTEL (OpenTelemetry) to the Aspire dev dashboard locally and to Azure Monitor in production, and emit LLM cost telemetry on every model call.
Stand up the auth gateway: Traefik with ForwardAuth in containers, Microsoft Entra ID by default, with Auth0, Okta, Google Workspace OIDC, AWS Cognito, or generic OIDC as first-class alternates when the client's identity posture calls for it.
Pair-program with the second engineer on the engagement under Maker-Checker. Solo delivery is not a PTM pattern.
Address the blockers that prevent AI from reaching enterprise-grade maturity in real environments: data readiness, integration complexity, state management, identity boundaries, observability gaps, and LLM cost runaway.
Feed lessons back into PTM's living digital twin — the Fusion Covenant, the persona library, the agentic-coding template, the methodology. Every engagement you ship updates our rules.