Lead Software Engineer (Go/Ruby) - Lab Automation

• 5+ years of experience in software engineering, with a proven track record in a lead or senior role
• Background in lab automation context (device integration) and Business Process Automation (BPA/rules engines)
• Proficiency in Go (Golang)
• Expertise in Ruby on Rails and Phoenix Framework
• Knowledge of relational databases (PostgreSQL, Oracle), NoSQL, and key-value stores
• Skills in building APIs using REST, GraphQL, and gRPC
• Familiarity with AWS services, including Elastic Container Service (ECS), Simple Storage Service (S3), and Application Load Balancer (ALB)
• Competency in Infrastructure as Code (Terraform), Docker containerization, and CI/CD pipelines (Jenkins)
• Advanced understanding of Git, code review best practices, and branching/merging strategies
• Qualifications in Unit testing, Integration testing, and Test-Driven Development (TDD)
• Experience with Agile methodologies (Scrum, Kanban) and continuous learning adaptability
• Proven experience in ITIL-managed organizations, strong problem-solving/debugging skills, and excellent cross-functional communication
• Excellent command of written and spoken English (B2+ level)

Nice to have:

• Hands-on experience with LIMS (Laboratory Information Management Systems)

• Architect robust, standardized integration layers (adapters/services) aligning automation systems (robots/instruments) tightly with LIMS workflows
• Implement fault-tolerant patterns, state management, and recovery mechanisms for device/network failures
• Deliver comprehensive monitoring, logging, and device telemetry
• Design, model, and govern a scalable, decoupled business rules engine ensuring rules are versioned, traceable, and safely deployable without disrupting operations
• Build scalable, modular systems with independent frontend/backend evolution incorporating caching, async processing, and secure-by-design practices
• Define and document contract-first APIs with proper versioning and secure interfaces
• Ensure full auditability and end-to-end traceability of all experimental data flows
• Coach engineers via code reviews, pair programming, and architecture walkthroughs
• Foster autonomy, knowledge sharing, and full-stack system thinking across the team
• Drive features end-to-end, prioritize tasks, manage time effectively, and consistently meet deadlines

EPAM is global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, we empower our clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.