Senior Systems​/Backend Engineer

Satomic’s mission is to close the gap from idea to molecule with faster navigation of chemical space. We are building an automated chemistry platform that integrates laboratory robotics, software, and AI to transform small-molecule synthesis and drug discovery.

As an early-stage startup, we are not only building the technology but also the playbooks, partnerships, and culture that will shape a new paradigm for drug discovery and chemistry at scale.

This role is critical to Satomic’s mission of closing the gap from idea to molecule by building the core software systems that turn customer intent into reliable, executable chemical reality. In executing our mission, Satomic is building an API to Atoms and this role ensures the software behind that API gives a clear, frictionless experience for users who depend on it to solve some of the most important challenges in medicine and human health.

On-site is preferred, but fully remote is also acceptable, with travel to San Diego expected ~1–2 times per year

We are seeking a Senior Systems / Backend Engineer to own and build the execution backbone of Satomic’s automated synthesis platform. This role is responsible for designing, implementing, and owning the systems that translate molecule requests into existing instrument-executable reaction planning software, schedule real laboratory assets, orchestrate long-running workflows, and track progress and failures end-to-end.

You will be the technical owner of long-running, stateful systems that must operate under real-world constraints: limited inventory, procurement delays, instrument scheduling conflicts, partial failures, laboratory retries, and re-work.

This is a hands‑on execution‑focused role for a senior engineer who has previously owned backend systems in production, understands how systems break as they scale, and is comfortable making architectural tradeoffs with incomplete information. You will partner closely with chemistry, automation, and data colleagues as a technical peer, with significant ownership over system design and outcomes.

This role prioritizes building correct, working systems first, with thoughtful evolution toward scale as real usage and constraints emerge. We value engineers who can distinguish between what must be robust from day one and what can be intentionally deferred.

This role does not own machine‑learning model development or data science, but does own how those components are integrated into robust, production workflows.

By day 30, you will have:

• Produced a documented workflow diagram of Satomic’s synthesis execution lifecycle, from compound request through planning, laboratory execution, failure handling, and delivery, clearly identifying the inputs, outputs, system boundaries, and state transitions at each step.
• Completed a written review of the existing backend systems and infrastructure, outlining what to keep, what to evolve, and what to change, with the key risks, tradeoffs, and reasoning behind those recommendations.
• Shipped a tightly scoped, user‑facing backend feature in the existing system that research operations currently use, without introducing major architectural changes.

By day 90, you will have:

• Produced a written execution architecture for workflow orchestration and state management, including a diagram and accompanying documentation that define system boundaries, core abstractions, ownership of state, explicit failure and retry behavior, and which design decisions are intentionally deferred.
• Delivered an MVP execution pipeline for Satomic’s production process, integrating synthesis planning, inventory, purchasing, and laboratory execution systems to support synthesis workflow from molecule request through delivery.
• Implemented a state‑machine–driven, event‑based execution model for the production MVP, with explicit states, transitions, and failure/retry behavior for a long‑running, multi‑step molecule delivery workflow.
• Established and documented backend engineering standards in active use for the production execution system, covering testing strategy, error handling, retries, and observability.
• Reduced manual intervention required…