Senior Software Engineer, Edge & Cloud Platform

illumicell AI; Boston (MA); Remote; USD 180,000 - 240,000; Full time

Job summary

illumicell AI is building a holographic imaging system for automated semen analysis, delivering clinically deliverable results from a Linux-based microscope scanner to cloud-based ML analysis. You will develop the software that connects the scanner to cloud reconstruction and ML analysis, handling device control, data safety, and end-to-end integration in a hands-on product role.

You will work with an existing senior engineer focusing on edge and cloud logic, interfaces, and end-to-end

Qualifications

• Substantial professional experience building/operating production software systems with clear ownership.
• Strong Python skills and solid API/data contracts, debugging judgment.
• Experience bridging device and cloud boundaries, backend and hardware, or data/control planes.
• Practical understanding of idempotency, retries, state machines, event-driven processing, concurrency, and observability.
• Strong testing practices: unit/integration/contract tests and CI/CD.
• Ability to work from incomplete goals, define scope, and progress without full spec.
• History of completing difficult integration work, not just prototyping.
• Comfortable using coding agents as tools while maintaining accountability.
• Clear English communication with software, ML, hardware, clinical, and product teams.
• Senior candidates typically 5+ years; degree is helpful but not required.

Responsibilities

• Own major edge and cloud product capabilities from problem definition to deployed behavior.
• Build Linux edge services with explicit state, resilient storage, and hardware-aware failure handling.
• Design/implement versioned REST/JSON/event/storage contracts across scanner, UI, and cloud.
• Develop cloud logic for scan reservation, admission, job lifecycle, and retries.
• Handle repeated events and network issues with idempotency and explicit state transitions.
• Integrate ML components into a single acquisition-scoped worker with stable interfaces.
• Create tests, emulators, hardware-in-the-loop, and cloud tests that exercise real failure modes.
• Add structured logs, metrics, alerts, and reconciliation for detectability of issues.
• Collaborate with ML, cloud infra, hardware, clinical, cybersecurity, and regulatory teams.
• Use coding agents for automation and maintain technical accountability for outputs.
• Tackle adjacent engineering work when it accelerates feature completion.

Skills

Python

Software design

Debugging

English comms

Problem-solving

Tools

FastAPI

OpenAPI

JSON Schema

Pydantic

Terraform/OpenTofu

GitLab CI

Docker

NVIDIA Jetson

Linux

Job description

illumicell AI is a medical-technology startup building AI-powered, label-free cell analysis to bring fast, objective diagnostics to the point of care. Based at the Pagliuca Harvard Life Lab, Harvard's startup incubator in Allston, we work at the intersection of optics, machine learning, and clinical medicine, surrounded by the research community our technology grew out of.

Starting with male fertility, we're developing a new standard for how living cells are measured, understood, and acted upon. We have a functional prototype device, a digital holographic scanner paired with cloud-based AI analysis, already producing live-cell measurements, and we are rapidly accelerating toward FDA submission. We're backed by Accel and Tim Draper, are Techstars alumni, and are building the team that will carry the product from working prototype to cleared clinical device.

About the Role

illumicell AI is building a holographic imaging system for automated semen analysis. The product begins with a Linux-based microscope scanner that captures live-cell video and ends with a clinically deliverable result: sperm concentration, motility, and eventually morphology, returned to the fertility lab. Between those two points is the platform this role is responsible for.

We are looking for a Senior Software Engineer to build and maintain the software that connects the scanner to cloud-based image reconstruction and machine learning analysis, and returns a reliable result to the clinic. That means device control and image acquisition, patient-safe data handling, resilient upload, cloud job orchestration, GPU analysis integration, result delivery, and the observability and test infrastructure to keep the whole path working.

This is a hands-on product role, not a DevOps or internal-tooling position. You will write production software across Linux-based edge devices and cloud services, define the interfaces between them, and carry difficult work through integration and verification. You do not need equal expertise in every layer, but you should be able to learn adjacent technologies and contribute wherever the work is most pressing.

You will work alongside an existing senior engineer who leads GCP, infrastructure, IAM, device-identity, deployment, and ML-infrastructure work. This role adds a second senior product-systems path and initially emphasizes edge and cloud application logic, interfaces, end-to-end integration, and shared review. It is not a replacement role. Level may flex to Staff for a candidate who has demonstrated technical direction across device, cloud, and infrastructure teams.

What You Will Build

The scanner captures ordered monochrome frames, removes patient identity before anything leaves the device, and uploads the encoded acquisition. The cloud verifies and admits the package, runs one GPU analysis job, and returns a de-identified result to the originating device, where identity is restored and the report is delivered to the clinic. Near-term work includes:

• A restart-safe edge controller and explicit scan state machine
• Camera acquisition running as a testable service rather than an interactive prototype
• Lossless PNG or FFV1 packaging, checksums, manifests, and resumable transfer to GCS
• An on-device patient-identity boundary and tokenized device-to-server contract
• Device-local REST and event-stream APIs for the operator interface and test automation
• An authenticated cloud control and admission API
• Event-driven cloud processing using GCS, Eventarc, Firestore, and Cloud Run Jobs
• Idempotent job launch, immutable result publication, retries, reconciliation, and cleanup
• Model and configuration provenance across reconstruction and ML analysis steps
• CI, structured observability, security controls, dependency records, and regulated traceability

Responsibilities

• Take responsibility for major edge and cloud product capabilities from problem definition through deployed and tested behavior.
• Build services and libraries for Linux edge devices with explicit state, resilient local storage, and hardware-aware failure handling.
• Design and implement versioned REST, JSON, event, and storage contracts between the scanner, operator interface, cloud control plane, and analysis worker.
• Build cloud application logic for scan reservation, admission, job lifecycle, result state, retries, and recovery.
• Handle repeated events and uncertain network conditions through idempotency, conditional writes, immutable artifacts, and explicit state transitions.
• Integrate reconstruction and ML components into one acquisition-scoped worker with stable typed interfaces rather than a chain of network services.
• Build contract, component, integration, emulator, hardware-in-the-loop, and representative-cloud tests that exercise real failure modes, not only the expected path.
• Add structured logs, metrics, alerts, and reconciliation so that a disabled trigger, stalled scan, or duplicate execution does not go undetected.
• Collaborate with ML engineers, the cloud infrastructure lead, hardware, clinical, cybersecurity, and regulatory contributors.
• Use coding agents and engineering automation to accelerate implementation, testing, investigation, documentation, and traceability work, reviewing generated changes critically and verifying behavior before accepting them.
• Take on adjacent engineering work when it is the clearest path to completing a product feature.

Required Qualifications

• Substantial professional experience building and operating production software systems, with clear ownership of the behavior, reliability, and delivery of those systems.
• Strong Python skills and solid software-design, API, data-contract, and debugging judgment.
• Experience on both sides of at least one meaningful system boundary: device and cloud, service and infrastructure, backend and hardware, or data plane and control plane.
• Practical understanding of idempotency, retries, state machines, event-driven processing, object storage, concurrency, failure recovery, and observability.
• Strong testing practices: unit tests, integration tests, contract tests, and CI/CD.
• Ability to work from an incompletely specified goal, define a reasonable scope, identify the decisions that need broader input, and make progress without waiting for a complete specification.
• A history of completing difficult integration work, not only designing or prototyping it.
• Comfortable using coding agents as engineering tools while retaining technical accountability for the output.
• Clear communication in English with software, ML, hardware, clinical, and product collaborators.
• Strong Senior candidates typically have five or more years of relevant professional experience; candidates with fewer years and directly applicable depth are also considered. A relevant degree is useful but not required.

Preferred Qualifications

• Google Cloud, particularly GCS, Eventarc, Firestore, Cloud Run, Cloud Run Jobs, Cloud Scheduler, Secret Manager, Artifact Registry, Cloud Logging, and IAM.
• FastAPI, OpenAPI, JSON Schema, Server-Sent Events, or Pydantic-based typed contract tooling.
• Terraform or OpenTofu, GitLab CI, Workload Identity Federation, Docker containers, and GPU jobs.
• Linux device software: NVIDIA Jetson, Raspberry Pi, USB/UVC cameras, V4L2, GPIO, process supervision, local state persistence, or store-and-forward data handling.
• Image or video acquisition, FFmpeg, FFV1, lossless data handling, scientific instruments, or GPU processing pipelines.
• Medical-device software, laboratory systems, patient-identity boundaries, IEC 62304, design controls, or evidence-based development practices.
• Result delivery interfaces such as SMB file shares, HL7v2/MLLP, FHIR, SMART Backend Services, LOINC, or UCUM.
• TypeScript or a modern web framework for a limited on-device operator interface.
• Background in robotics, IoT, industrial automation, scientific instruments, imaging systems, or healthcare software, where device software and cloud services must function together as a single product.

Our Technical Environment

Current stack: Python 3.12, FastAPI, Pydantic, PyTorch, Detectron2, OpenCV, GCS, Eventarc, Firestore, Cloud Run, Cloud Run GPU Jobs, Cloud Scheduler, Artifact Registry, Secret Manager, Cloud Logging, Docker, Terraform/OpenTofu, GitLab CI, and a modular monorepo. We use the smallest architecture that preserves the intended product behavior and recovery model. Interfaces, versions, tests, and failure behavior are product features, not afterthoughts.

Location & Hours

This role is based in the Boston or San Francisco Bay Area, where most of our team and collaborators are located, and candidates in those areas are preferred. We are open to fully remote candidates within the United States for the right person.

We work on Eastern Time with flexible hours. There are no fixed daily hours; we ask for reliable overlap with the team during core Eastern Time working hours for reviews, pairing, and clinical-collaborator meetings.

All applicants must be authorized to work in the United States. illumicell AI is currently not sponsoring visas. Applications will be accepted on an ongoing basis. Flexible (unlimited) paid time off.

illumicell AI is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, and gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable federal, state, or local law. If you require a reasonable accommodation during the application or interview process, please let us know when you apply.