Scientific AI Engineer

We are seeking an autonomous Scientific AI Engineer who will work closely with the existing ImmGen computational team and immunologists to design and implement this agent. They will integrate ImmGen’s existing data resources and analytical capabilities with the AI-powered interface. They will not be expected to acquire or manage ImmGen data, nor rebuild analytical tools. Instead, they will determine how to expose, adapt, orchestrate, and extend those tools so they can be reliably accessed through natural-language interaction, using MCP strategies that can be exploited by AI agents.

The position will:

• Work closely with ImmGen scientists and data analysts to understand existing datasets, metadata, documentation, tools, APIs, and access mechanisms, adapt and wrap existing ImmGen data so they can be invoked reliably by LLM-based agent that calls on public analytical and visualization tools.
• Collaborate with ImmGen scientists to define supported use cases, desired answer formats, and appropriate scientific language and graphics.
• Map existing and potential researcher questions to the appropriate existing ImmGen resources and analytical workflows.
• Develop the software interfaces, APIs, schemas, computational guardrails and orchestration logic required to connect the agent to ImmGen’s existing infrastructure.
• Implement safeguards against hallucinated results, invalid comparisons, inappropriate statistical interpretations, and unsupported biological claims.
• Ensure that the agent does not automatically initiate unduly expensive computes.
• We are looking for a team player eager to participate in the exciting re-writing of scientific data propagation.

Basic Qualifications:

• Minimum of five years’ post-secondary education or relevant work experience.

Additional Qualifications and Skills:

• Advanced degree or equivalent professional experience in computational biology, bioinformatics, genomics, or a related field.
• Strong Python programming skills and experience with scientific computing libraries such as pandas, NumPy, SciPy, scikit-learn, Scanpy, Bioconductor, or equivalent tools.
• Strong software-engineering skills, including experience with APIs, data schemas, testing, version control, logging, documentation, and reproducible workflows.
• Experience integrating software with existing scientific data platforms, analytical pipelines, web services, or computational tools.
• Hands-on experience with LLM applications, including tool/function calling, retrieval-augmented generation, structured outputs, agent orchestration, or natural-language-to-SQL/code systems.

• Term: This is a 2-year term position from the date of hire, with the possibility of extension, contingent upon work performance and continued funding to support the position.
• Standard Hours/Schedule: 35 hours per week.
• Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position.
• Pre-Employment Screening: Identity
• Interview Format: The interview process will include both virtual and in-person components (e.g., initial virtual screening followed by on-campus final interviews).
• Staying Informed About Your Application: Due to the high volume of applications, we may not always be able to reach out right away, but you can track your status anytime through the Careers@Harvard portal.

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Work Format Details

This position has been determined by school or unit leaders that all duties and responsibilities must be performed at a Harvard or Harvard-designated location. Certain visa types may limit work location. Individuals must meet work location sponsorship requirements prior to employment.

Salary Grade and Ranges

This position is salary grade level 057. Please visit  Harvard's Salary Ranges  to view the corresponding salary range and related information.

Benefits

Harvard offers a comprehensive benefits package that is designed to support a healthy work-life balance and your physical, mental and financial wellbeing. Because here, you are what matters. Our benefits include, but are not limited to:

• Generous paid time off including parental leave
• Medical, dental, and vision health insurance coverage starting on day one
• Retirement plans with university contributions
• Wellbeing and mental health resources
• Support for families and caregivers
• Professional development opportunities including tuition assistance and reimbursement
• Commuter benefits, discounts and campus perks

Learn more about these and additional benefits on our Benefits & Wellbeing Page.

EEO/Non-Discrimination Commitment Statement

Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard's academic purposes.

Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy. Harvard's equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.