Sr. Automation Engineer

Zifo•Boston, MA

About The Position

Zifo is a global specialist scientific and process informatics services company supporting life sciences, biotech, and pharmaceutical organizations. We enable digital transformation across R&D, manufacturing, and quality by delivering data-driven, scalable, and compliant software solutions. Zifo is seeking an experienced Scientific Automation Lead to drive the design, architecture, and delivery of scalable, compliant automation solutions across scientific and laboratory workflows. The role sits at the intersection of science, laboratory informatics, data, integration, cloud, and automation technologies, partnering with scientists, laboratory users, technical teams, and client stakeholders to identify automation opportunities and translate complex experimental workflows into robust, production-ready solutions spanning scientific system integrations, data components, workflow orchestration, AI-enabled capabilities, and next-generation data pipelines. The Automation Lead will provide technical leadership across solution architecture, integration strategy, automation frameworks, testing, CI/CD, production readiness, and delivery, while mentoring engineering teams, establishing reusable automation patterns and accelerators, managing technical dependencies, and serving as a key technical interface with clients. Experience with Benchling, LIMS, ELN, SDMS, CDS, enterprise data platforms, and strong expertise in Python, APIs, AWS, and modern software engineering practices will be highly valued.

Requirements

Bachelor’s or Master’s degree in engineering, Life Sciences, or a related field
6+ years of experience in automation, software engineering, and technical development
3+ years of experience in customer/client engagement and relationship management
3+ years of experience in technical/team leadership and mentoring
Strong hands-on experience with Python, FastAPI, REST APIs, microservices, automation frameworks, and scientific/enterprise system integrations, with experience using frameworks and tools such as pytest, Apache Airflow, Prefect, or equivalent workflow orchestration 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, and system integrations.
Strong understanding of Git, CI/CD, automated testing, Docker, DevOps, and modern software development practices.
Experience with testing frameworks such as pytest/unittest, including unit, integration, API, and end-to-end testing.
Working knowledge of AI/ML concepts and data/ML libraries such as pandas, NumPy, and scikit-learn; TensorFlow/PyTorch is a plus.
Strong understanding of software architecture, design patterns, integration patterns, Agile/Scrum, SDLC, and cloud deployment practices.
Experience working in regulated environments, with knowledge of GxP, 21 CFR Part 11, data integrity, audit trails, validation, and change management.
Demonstrated ability to lead technical teams, mentor engineers, conduct technical reviews, and establish engineering standards.
Strong communication, stakeholder management, problem-solving, client-facing, and cross-functional leadership skills.

Nice To Haves

Experience working with global, geographically distributed teams and managing cross-team dependencies.
Experience with scientific and laboratory systems such as Benchling, LIMS, ELN, SDMS, CDS, or similar platforms; life sciences/pharmaceutical experience preferred.
Experience developing reusable automation frameworks, accelerators, and integration patterns.
Experience working directly with scientists, assay teams, laboratory users, and business stakeholders.
Experience with technical estimation, client workshops, discovery sessions, solution proposals, or pre-sales activities.
Willingness to travel/ relocate based on project or business needs

Responsibilities

Own end-to-end automation initiatives, from discovery, technical assessment, and solution strategy through architecture, implementation, deployment, and production support, ensuring solutions are scalable, reusable, and aligned with business and scientific objectives.
Drive the development of integrated automation solutions across laboratory workflows, scientific systems, data platforms, workflow orchestration, and AI/ML capabilities, collaborating effectively with scientists, technical teams, and client stakeholders.
Design and develop automation frameworks, APIs, microservices, integrations, and data pipelines using Python, FastAPI, AWS, and modern cloud technologies.
Lead integration with scientific and enterprise platforms such as Benchling, LIMS, ELN, SDMS, CDS, and enterprise data platforms using API, file-based, event-driven, and other integration patterns.
Drive automation of data ingestion, transformation, validation, reconciliation, workflow execution, and data movement across laboratory and downstream systems.
Establish reusable frameworks, components, accelerators, and engineering standards, while leading testing, CI/CD, deployment, monitoring, troubleshooting, and production-readiness practices.
Ensure solutions meet security, data integrity, performance, auditability, and regulatory requirements, including GxP and 21 CFR Part 11 where applicable.
Provide technical leadership and mentorship through architecture and design reviews, code reviews, technical problem solving, performance optimization, and guidance to automation engineers.
Manage technical delivery, including estimates, dependencies, risks, resource needs, cross-team coordination, and delivery status across geographically distributed teams; serve as a technical point of contact for clients and communicate solution approaches, recommendations, and trade-offs.
Drive continuous improvement and innovation by evaluating automation, AI/ML, workflow orchestration, and cloud technologies, while maintaining clear technical documentation covering architecture, integrations, APIs, workflows, testing, deployment, and operations using JIRA, Confluence, or equivalent tools.