Sr. Automation Engineer

Responsibilities

• Own end-to-end scientific automation initiatives from discovery and solution strategy through architecture, implementation, deployment, and production support.
• Design and develop automation frameworks, APIs, microservices, integrations, data pipelines, and workflow orchestration using Python, FastAPI, AWS, and related technologies.
• Integrate laboratory and enterprise platforms such as Benchling, LIMS, ELN, SDMS, CDS, and enterprise data platforms using API, file-based, and event-driven patterns.
• Lead data ingestion, transformation, validation, reconciliation, workflow execution, and data movement across laboratory and downstream systems.
• Establish reusable engineering frameworks, components, accelerators, standards, testing, CI/CD, deployment, monitoring, and production-readiness practices.
• Ensure solutions meet security, data integrity, performance, auditability, GxP, and 21 CFR Part 11 requirements where applicable.
• Mentor automation engineers and provide technical leadership through architecture reviews, code reviews, technical problem solving, and performance optimization.
• Manage technical dependencies, risks, estimates, resources, cross-team coordination, delivery status, and client-facing technical communication.
• Maintain technical documentation for architecture, integrations, APIs, workflows, testing, deployment, and operations using JIRA, Confluence, or equivalent tools.

Requirements

• Bachelor’s or master’s degree in engineering, life sciences, or a related field, with 6+ years of experience in automation, software engineering, and technical development.
• At least 3 years of customer or client engagement and relationship-management experience and 3 years of technical or team leadership and mentoring experience.
• Strong hands-on experience with Python, FastAPI, REST APIs, microservices, automation frameworks, and scientific or enterprise system integrations.
• Experience with pytest, unittest, Apache Airflow, Prefect, or equivalent workflow orchestration and testing technologies.
• Strong experience with SQL, data modeling, relational databases, and familiarity with NoSQL databases.
• Strong AWS experience, including S3, EC2, Lambda, Step Functions, RDS/Aurora, IAM, monitoring, and logging.
• Experience with data pipelines, ETL/ELT, data validation, workflow automation, system integrations, Git, CI/CD, Docker, and modern software development practices.
• Experience with unit, integration, API, and end-to-end testing.
• Working knowledge of AI/ML concepts and libraries such as pandas, NumPy, and scikit-learn; TensorFlow or PyTorch is a plus.
• Understanding of software architecture, design patterns, integration patterns, cloud deployment, regulated environments, GxP, 21 CFR Part 11, audit trails, validation, and change management.
• Demonstrated ability to lead technical teams, mentor engineers, conduct technical reviews, establish engineering standards, and communicate with clients and stakeholders.
• Experience with global distributed teams, scientific or laboratory systems, life sciences or pharmaceutical environments, client workshops, discovery sessions, solution proposals, or pre-sales activities is preferred.
• Willingness to travel or relocate based on project or business needs.

Benefits

• Hybrid work arrangement in Boston, United States.
• Accrued vacation, medical, dental, and vision insurance.
• 401(k) with company matching, life insurance, and flexible spending accounts.
• Competitive compensation package and an employee-built, science-focused work culture.