This opportunity is with a exciting start-up business building an AI-driven drug-development platform that fuses multi-omics data with graph neural networks, knowledge graphs and agentic workflows to accelerate therapeutic development. Their stack pairs a user-facing app with a dedicated Graph Service running GPU-accelerated analytics (PyTorch Geometric, cuDF/cuGraph) on AWS, and leverages Bedrock for LLMs within orchestrated, tool-using agents (LangGraph).
About the Role
You'll be the first dedicated software engineer, working directly under the CTO and taking work off his desk across the full stack - the user-facing app, the services behind it, the infrastructure it runs on, and the security posture around all of it. The science is ahead of the software, and your job is to close that gap. This is a founding role in the real sense. You won't be handed tickets, you'll be handed problems, and the decisions you make in the first six months will still be load-bearing three years from now. We're less interested in someone who pushed the button than someone who built the button.
Responsibilities
- Own the user-facing app end to end - architecture, implementation, and the UI/UX decisions inside it. Your users are computational biologists and bioinformaticians who will tell you plainly when something wastes their time.
- Build and own the backend services (Flask/FastAPI microservices) and the APIs between the app, the Graph Service and our data layer.
- Design data-dense interfaces for scientific work - large result sets, provenance, and analyses that need to be inspectable rather than merely pretty.
- Own the infrastructure: Terraform, Docker, GitHub Actions, and the AWS footprint (EC2, RDS, SageMaker, Bedrock, graph DBs). Including cost - on our runway, compute discipline is a survival skill.
- Drive security-minded engineering and SOC 1 / SOC 2 readiness: least-privilege IAM, secrets management, encryption, audit trails, data handling and reproducibility. We work with sensitive biological data and partner data covered by real contracts, and you'll be the engineer who can prove our posture to a pharma partner's security team.
- Plumb the agentic workflows - the app-side and service-side surfaces that LangGraph orchestration and Bedrock model calls hang off, instrumented with logging and tracing.
- Deliver directly to partners. At our size the engineer who builds it is the engineer who ships it. You'll be on calls with pharma partners and CROs, handling data exchange, packaging results, and fixing what's wrong in front of them.
- Decide what not to build. You'll have more good ideas than runway. Choosing correctly is most of the job.
Qualifications
- 5+ years building and shipping production software (or equivalent impact), including something you took from nothing to live.
- Deep proficiency in Python with strong software engineering fundamentals.
- Genuine full-stack range - you can design a schema in the morning and make an interface usable in the afternoon, and consider neither beneath you.
- Practical AWS experience with at least some of: EC2, RDS (or similar managed DBs), S3, IAM, and container or serverless compute. You've made architecture and cost decisions and lived with them.
- Working knowledge of Docker and infrastructure as code (Terraform or equivalent), and CI/CD you've actually maintained.
- Security instincts you apply unprompted: least-privilege access, secrets that never touch git, encryption in transit and at rest, audit logging - and the understanding that a hash of an identifier is not anonymisation.
- Startup experience, ideally somewhere small and fast, where you owned outcomes rather than tickets.
- Comfort being the only person in the room who thinks like an engineer. You'll be outnumbered by PhDs roughly six to one, and you need to enjoy that.
Required Skills
- Background working with omics datasets or adjacent bio/healthcare data; comfort reading domain literature.
- Data provenance and reproducibility as instincts - versioned datasets, pinned environments, stable identifiers, and the assumption that every number should be traceable to the run that produced it.
- Ability to read a bioinformatics pipeline (Nextflow, Snakemake, WDL) well enough to wrap it, schedule it and surface its output. Our bioinformaticians write them.
- Prior exposure to SOC 1 / SOC 2 programmes - ideally as the engineer producing the evidence rather than a bystander.
- Experience handling regulated or special-category data; you can discuss pseudonymisation versus anonymisation without hand-waving.
- Enterprise-readiness work: SSO/SAML, SCIM, RBAC, audit log export, tenant isolation for partners who won't share infrastructure.
- Forward-deployed instincts - you've built directly alongside a customer and know which bespoke work to fold back into the product.
- LangGraph / LangChain or comparable agentic orchestration experience; observability and experiment tracking (MLFlow, Weights & Biases).
Preferred Skills
- AWS: EC2, RDS, S3, Bedrock, SageMaker, (optionally) AWS graph DBs
- Backend & Services: Python, Flask/FastAPI microservices, Docker, Terraform, GitHub Actions, Nginx/Gunicorn
- Frontend: modern JS/TS app framework - (CONFIRM: name the framework in use)
- ML/Systems: PyTorch, PyTorch Geometric, CUDA, cuDF, cuGraph, (NetworkX equivalents)
- Tooling: heavy use of AI coding tools, Claude Code included - we expect fluency, and opinions about where it helps and where it quietly lies to you