Principal Engineer at Flagship Pioneering, Inc.

About the role Flagship Pioneering is seeking a highly experienced Principal Software Engineer to join their dedicated team focused on developing the digital and AI platform that supports drug discovery and scientific research within the Flagship ecosystem. This role is designed for a senior-level engineer who will take ownership of critical system components, lead architectural decisions, and collaborate closely with scientists and machine learning researchers to build scalable, reliable, and innovative software solutions. The successful candidate will act as a technical leader, overseeing system design, implementation, and integration efforts, ensuring that the platform meets the high standards required for scientific and AI-driven applications. Reporting directly to the Vice President of Engineering, this position offers an opportunity to influence the future of scientific software infrastructure and contribute to groundbreaking advancements in biotech research.

Key facts

Location: Cambridge, MA USA Engagement: Full-time Team: Pioneering Intelligence

What you'll do

- Lead the design and development of the technical architecture for one or more AI-driven product areas within the Pioneering Intelligence platform, which includes scientific workflow tools, data infrastructure, and AI integration components.
- Take ownership of building production-grade systems from initial concept through deployment, scaling, and ongoing maintenance, ensuring robustness, security, and performance.
- Collaborate directly with scientific teams and machine learning researchers to understand their needs, workflows, and challenges, translating these into effective software solutions that enhance research productivity and decision-making.
- Make critical technical decisions regarding system architecture, data pipelines, API design, and AI component integration, balancing innovation with reliability and scalability.
- Work closely with product managers, ML scientists, and other stakeholders to shape product strategy, prioritize features, and define technical roadmaps aligned with scientific goals.
- Conduct architectural reviews and code reviews to maintain high engineering standards, identify potential failure points, and implement best practices for distributed systems and AI-native engineering.
- Apply AI-native engineering tools and methodologies to improve system efficiency,



facilitate experimentation, and support the deployment of machine learning models into production environments.
- Occasionally oversee the work of embedded software engineering contractors, providing technical guidance, reviewing deliverables, and ensuring alignment with project goals and quality standards.
- Participate in cross-functional team meetings, contribute to technical documentation, and communicate complex technical concepts clearly to both technical and non-technical stakeholders.
- Stay current with emerging trends in AI, machine learning, and software engineering, and evaluate their applicability to the platform's development roadmap.
- Foster a culture of high-quality engineering, continuous improvement, and innovation within the team, mentoring junior engineers and promoting best practices.

Requirements

- Proven experience as a technical lead or principal engineer on complex, production-level systems, demonstrating ownership of architecture, design, and implementation.
- Extensive background developing software that is used by researchers or scientists for critical decision-making processes, with a deep understanding of their unique needs and workflows.
- Demonstrated experience designing and deploying systems that incorporate machine learning or AI components in a production environment, including data pipelines, model serving, and API integration.
- Strong knowledge of distributed systems, scalable data infrastructure, and cloud-based deployment strategies.
- Ability to thrive in fast-paced, ambiguous environments where requirements may evolve rapidly, and priorities shift frequently.
- Excellent problem-solving skills, with a focus on identifying root causes and implementing effective solutions in complex systems.
- Strong collaboration skills, with experience working closely with ML scientists, research teams, and product managers to translate scientific models into reliable software products.
- Proficiency in evaluating architectural choices,



identifying potential failure points, and designing resilient systems.
- Ability to communicate technical concepts clearly and effectively, both verbally and in writing, including creating design documents, architecture diagrams, and API specifications.
- Commitment to writing clean, well-documented, and thoroughly tested code, following best engineering practices.

Nice to have

- Familiarity with AI-native engineering practices, including working with large language models (LLMs) and understanding their capabilities and limitations.
- Experience with containerization, orchestration tools such as Kubernetes, and cloud platforms like AWS, GCP, or Azure.
- Knowledge of scientific or research software development, especially in biotech or pharmaceutical contexts.
- Understanding of data privacy, security standards, and compliance requirements relevant to scientific data and AI applications.
- Experience mentoring junior engineers and fostering a collaborative, innovative engineering culture.

Skills & tools

- Strong system design and architecture evaluation skills.
- Expertise in AI-native engineering, including deploying and maintaining machine learning models in production.
- Proficiency in programming languages such as Python, Java, or similar, with an emphasis on writing clean, maintainable code.
- Familiarity with data infrastructure tools, APIs, and cloud deployment strategies.
- Excellent debugging, troubleshooting, and performance optimization skills.
- Ability to create clear technical documentation, design diagrams, and API contracts.
- Knowledge of testing frameworks, CI/CD pipelines, and automated deployment processes.

Practical notes

The salary range for this position is $188,000 - $258,500. Compensation will be determined based on the candidate's qualifications, skills, and experience.

Flagship Pioneering offers comprehensive healthcare coverage, an annual incentive program, retirement benefits, and a variety of additional perks designed to support employees' well-being and qualified growth.

This role is based on-site in Cambridge, MA, and requires working at the company's physical office location.

The company values innovation, collaboration, and technical excellence, providing an environment where senior engineers can make a significant impact on scientific research and biotech advancements.

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📌 Principal Engineer (Cambridge)
🏢 Flagship Pioneering
📍 Cambridge