Lead Platform Engineer

We are seeking two hands-on Lead Platform Engineers to help build and scale the backend and cloud infrastructure supporting a global DNA-sequencing operation., The role will initially be highly hands-on, with the engineer learning the existing systems and taking ownership of major technical areas. Over time, the position will transition into approximately:

• 70% hands-on architecture and software engineering
• 30% technical leadership, mentoring, and team leadership, The platform supports a globally distributed sequencing operation involving:
• Laboratory robots and DNA sequencers
• On-premises Linux infrastructure
• AWS cloud environments
• Terabytes of sequencing data movement
• Hundreds of thousands to millions of bioinformatics jobs
• Distributed queues and asynchronous workloads
• Workflow orchestration and scheduling
• Retry and failure-handling mechanisms
• Distributed state management
• Fault-tolerant production systems
• Large-scale compute infrastructure
• AI agents that interact with internal tools, APIs, operational data, and physical workflows

The infrastructure currently supports approximately 5,000 CPUs, 12.5 TB of RAM, and 100+ GPUs, with significant production AWS usage., * Design, build, and operate high-scale distributed backend and platform systems.

• Develop production backend services primarily using Python.
• Build and maintain cloud-native services and infrastructure on AWS.
• Design systems for asynchronous processing, distributed queues, workflow orchestration, scheduling, retries, state management, and fault tolerance.
• Build reliable systems for moving large volumes of data between laboratory equipment, on-premises infrastructure, and AWS.
• Develop services that orchestrate large numbers of compute and bioinformatics workloads.
• Design and implement scalable APIs, microservices, workers, and event-driven services.
• Work across application code, cloud infrastructure, Linux systems, data movement, and operational tooling.
• Architect and implement production systems from concept through deployment and ongoing operation.
• Troubleshoot complex production issues and improve system reliability, performance, and scalability.
• Lead major technical projects from design through production.
• Establish engineering patterns, standards, and best practices for a growing platform team.
• Mentor and provide technical guidance to engineers while remaining deeply hands-on.
• Collaborate with engineering, infrastructure, security, and scientific teams.
• Explore and implement practical applications of AI agents and modern AI development tools within production systems., * Python
• FastAPI, Django, or comparable Python backend frameworks
• REST APIs
• Microservices
• Event-driven architecture
• Asynchronous processing
• Backend service development

AWS & Cloud

• Amazon Web Services (AWS)
• ECS
• AWS Batch
• AWS Step Functions
• SQS
• Lambda
• Cloud-native architecture
• Infrastructure as Code
• Production cloud environments

Distributed Systems & Orchestration

• Distributed systems
• Distributed computing
• Task queues
• Job queues
• Message queues
• Workflow orchestration
• Job orchestration
• Scheduling
• Retry mechanisms
• State management
• Fault tolerance
• Failure recovery
• High-volume workload processing
• Event-driven services

The ideal candidate is a Senior or Staff-level engineer with strong Python, AWS, distributed-systems, and cloud-orchestration experience, who has worked in an early-stage startup environment and personally built systems from the ground up., * 6+ years of professional experience in backend engineering, platform engineering, infrastructure engineering, distributed systems, or closely related software engineering roles.

• Strong professional experience with Python backend development.
• Strong hands-on experience with AWS cloud infrastructure and services.
• Significant experience designing and building distributed production systems.
• Hands-on experience with task queues, asynchronous processing, event-driven systems, workflow orchestration, scheduling, retries, state management, and fault tolerance.
• Experience building systems from scratch or from early-stage prototypes through production.
• Meaningful experience working in an early-stage startup or rapidly scaling engineering environment.
• Demonstrated ownership of major technical systems or projects.
• Experience scaling systems, infrastructure, workloads, or engineering platforms as a company grows.
• Experience providing technical leadership and mentoring engineers.
• Strong Linux and cloud-infrastructure fundamentals.
• Ability and willingness to remain approximately 70% hands-on with architecture, coding, debugging, and production engineering., * Celery
• Amazon SQS
• Kafka
• RabbitMQ
• gRPC
• Similar distributed messaging or task-processing technologies

Infrastructure

• Linux
• Docker / containerized environments
• Cloud infrastructure
• Infrastructure automation
• Production monitoring and troubleshooting