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Senior Backend / Full-Stack Engineer (Contract)

Remote, United States

Peach Pilot: Senior Backend / Full-Stack Engineer (Contract)

Remote (US)  ·  Full-Time Contract  ·  ~5 hrs/day EDT Overlap  ·  3–6 Month Engagement  ·  Founding-Team Scope

The Company

Most AI companies sell tools. We transform how businesses run.

Peach Pilot builds a platform that ingests everything about how a company operates — every system, every process, every signal — and constructs a Company Brain: a living knowledge graph that connects people, decisions, and outcomes across the entire organization. We deploy 92 pre-built AI agents that work together across every business function, governed by humans at every critical step. The system gets smarter with every interaction.

We don't sell software licenses. We embed into a client's operation, learn their business in weeks, show them what's broken backed by their own data, and redesign their highest-impact business functions with AI. Our first vertical is insurance. Our first client engagement is already scoped and funded.

Peach Pilot is co-founded by Mario Montag (Predikto, acquired by a Fortune 50; McKinsey, PwC) and JP James (Hive Financial Assets, Georgia Tech, TITAN 100). We have a working platform with live infrastructure and a proven data-to-insights methodology.

The Role

This is a contract engagement to add senior engineering velocity to our founding team while we run our perm leadership search. We need an experienced engineer who can come in remotely, ship production code from week one, and pair directly with Mario and our fractional PM on the build.

The work is full-stack with founding-team scope, but its center of gravity is the backend: the async agent runtime, agent orchestration, ingestion pipelines, the knowledge graph, and the services that hold it all together. You'll also build the application layer that surfaces this to clients — but you don't need to be a frontend specialist. Design and interaction craft sit with our UX designer; we need you to ship the backend and wire the surface that exposes it. This is not a staff-aug seat. The right person operates like a founding engineer and is energized by ambiguous, high-leverage work.

We are building agentic-first software. AI agents are not a feature we are adding — they are the foundation we are building on from day one. You will be writing code in an environment where AI agents are driving the build, not assisting it. If you have been waiting for the right environment to work this way, this is it.

Open to a perm conversation if the engagement clicks for both sides — but the engagement stands on its own value without that conversion.

What You'll Own & Build

Backend & Agent Runtime

Own the Python services at the core of the platform — the async agent runtime, agent orchestration, multi-tenant APIs, and the data and knowledge-graph layer (Memgraph, Qdrant, Neo4j). This is where most of the work lives. You move up the stack as the build demands, but the backend is home.

Pipeline & Ingestion

Pick up live work across data ingestion and knowledge-graph integration that feeds the Company Brain. Ship discrete features end-to-end without an extensive ramp — you should expect to be in production code within the first week.

Agent Surface Area

Build the front-end and runtime layer that surfaces AI agent activity, recommendations, and human-in-the-loop governance to client users. Agents don't operate in the background — they communicate. You'll wire up and ship that surface so non-technical executives can read and trust it; the design itself sits with our UX designer.

Engineering Standards

Match the bar Mario and JP are setting on code quality, testing, and deployment. Leave the codebase better than you found it.

The Stack

  • AI/LLM: Anthropic Claude · OpenAI GPT · LiteLLM (multi-model routing) · Custom agent orchestration with reinforcement learning
  • Backend: Python (FastAPI) · Async agent runtime · JWT auth + multi-tenant isolation · Pydantic
  • Data & Graph: Memgraph · Qdrant · Neo4j · PostgreSQL · Redis
  • Frontend: React/Next.js · TypeScript · Tailwind CSS
  • Integrations: Nango (700+ connectors)
  • Infrastructure: Google Cloud Platform (Cloud Run, GCE, Firebase) · GitHub Actions CI/CD · Docker. We run on GCP — not Azure or AWS.
  • Helpful, not required: Plotly · D3 · Recharts for wiring up data visualizations (design and interaction craft are owned by our UX designer).

Who You Are

  • 7+ Years of Senior Engineering. You have shipped production systems at scale across multiple roles. You operate independently and have founding or early-team experience in your background.
  • Backend-Deep, Full-Stack-Capable. Your strength is Python — services, async agent runtime, APIs, and data/graph. You're comfortable enough in React/TypeScript to ship the agent-facing surface and you're not precious about which layer you're in, but the backend is where you live.
  • AI Production Experience. You have built or contributed to production LLM applications. You understand streaming responses, model uncertainty, and the realities of agent systems.
  • Knowledge Graph & Data-Intensive Production. You have worked with Memgraph, Neo4j, Qdrant, or comparable systems in production — and you can point to a specific modeling decision you made and why. You think in graphs and entities, not just rows.
  • Contract-Ready and Full-Time. US-based, available 40 hours per week with ~5 hours/day of EDT overlap, comfortable operating under a contract structure. This is a full-time contract engagement, not a fractional or moonlight seat. Open to perm conversion if the engagement goes well — but able to operate professionally without that as the goal.
  • Bias Toward Shipping. You move on the work in front of you. You don't wait for clarity that hasn't arrived yet.

What Makes This Different

You are joining a proven founder's second company with established domain credibility. We have a working platform with live infrastructure and a first client engagement already in motion. You will have access to production data, live workflows, and real compliance requirements from day one.

Every engagement makes the platform smarter. Every client's data enriches the knowledge base for the next one. You're not building features for a backlog — you're building the engine that transforms how companies operate.

We pay market rates for senior contract engineering. Conversion to full-time is on the table if the fit is right for both sides.

Engagement & Compensation

  • Hourly Rate: Negotiable, market-aligned for senior contract engineering
  • Engagement Length: 3–6 month initial contract
  • Conversion: Optional full-time conversion based on mutual fit
  • Hours: Full-time, 40 hours per week, with ~5 hours/day of EDT overlap
  • Location: Remote, US-based

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How are you actively using AI tools in your day-to-day engineering — agent workflows, Claude Code, automating your own dev loop? Be specific about one example: what you built or automated, what the workflow looks like now, and what measurably changed in your shipping speed or quality as a result.

Tell us about a non-technical user or team that struggled to adopt a tool or process you built or championed. What was the actual root cause was the product genuinely solving the right problem, or was the resistance telling you something the product wasn't fixing? How did you figure out the difference, and what did you do about it?

How do you test your own code today — and how does that practice shift when AI agents are generating significant portions of the code alongside you? Be specific about your TDD or eval-driven workflow and how you catch your own blind spots.

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This is a full-time contract engagement: 40 hours per week, US-based, 3 to 6 months, with optional FTE conversion. If you convert you might need to relocate to the Atlanta office.  Is this something you would consider? 

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Do you require any type of immigration sponsorship now or in the near future?