Forward Deployed Engineer - Software Development Engineer – Artificial Intelligence (AI) - #4883

GRAIL•Menlo Park, CA

8d•$86,000 - $121,000•Hybrid

About The Position

GRAIL is a healthcare company pioneering new technologies to advance early cancer detection. The Forward Deployed Engineer - Software Development Engineer – Artificial Intelligence (AI) is an experienced software engineer responsible for designing, developing, testing, deploying, and supporting AI-enabled software applications, machine learning solutions, and enterprise software platforms. Working under the guidance of senior technical leaders, this role contributes to the development of scalable, secure, and maintainable AI solutions that support GRAIL's scientific, clinical, laboratory, commercial, and enterprise initiatives. The Forward Deployed Engineer - Software Development Engineer partners with Software Engineering, Data Science, Product Management, Quality, Regulatory Affairs, Clinical Development, Laboratory Operations, Finance, Legal, People, and other cross-functional teams to develop innovative AI-powered solutions while ensuring software quality, operational reliability, and compliance with applicable standards. This role is expected to demonstrate technical ownership within assigned areas while continuing to develop expertise in AI engineering, software architecture, and cloud-native technologies. This role is based in Menlo Park, California, and will move to Sunnyvale, California in Fall 2026. It offers a flexible work arrangement, with the ability to work from GRAIL's office or from home. Our current flexible work arrangement policy requires that a minimum of 60%, or 24 hours, of your total work week be on-site. Your specific schedule, determined in collaboration with your manager, will align with team and business needs and could exceed the 60% requirement for the site. At our Menlo Park campus, Tuesdays and Thursdays are the key days where we encourage on-site presence to engage in events and on-site activities. We may also consider candidates in Durham NC but the bay area is preferred.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Data Science, or a related field.
Typically 3–5 years of professional software development experience, including experience developing enterprise applications or AI-enabled software solutions.
Experience with software development using Python and one or more programming languages such as Java, C#, C++, or JavaScript/TypeScript.
Working knowledge of cloud computing platforms (AWS, Azure, or GCP), APIs, microservices, containers, and modern software development practices.
Experience with CI/CD pipelines, source control systems, Agile development methodologies, and automated testing.
Familiarity with databases, data engineering concepts, REST APIs, and software integration.
Working knowledge of applicable security, privacy, and regulatory requirements relevant to software development, including: Cybersecurity fundamentals and secure software development practices, HIPAA and protection of sensitive data, FDA-regulated environments, software validation, and data integrity principles.
Solid software engineering skills with the ability to develop scalable, maintainable, and reliable software solutions.
Working knowledge of artificial intelligence, machine learning, Generative AI, and modern AI development techniques.
Strong analytical and problem-solving skills with the ability to troubleshoot technical issues independently.
Effective collaboration skills with cross-functional engineering, product, and business teams.
Strong written and verbal communication skills with the ability to explain technical concepts clearly.
Ability to learn new technologies quickly and adapt to changing business priorities.
Demonstrates ownership, accountability, and commitment to delivering high-quality software.
Continuous learning mindset with interest in emerging AI technologies and engineering best practices.

Nice To Haves

Experience working with AI or machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, OpenAI APIs, Azure OpenAI, Amazon Bedrock, or similar technologies is preferred.
Experience working in healthcare, biotechnology, diagnostics, life sciences, or regulated environments is preferred.
FDA-regulated software environments, software validation, and data integrity principles (preferred)

Responsibilities

Design, develop, test, deploy, and maintain AI-enabled software applications, machine learning services, APIs, and enterprise software solutions.
Develop software that leverages artificial intelligence, machine learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and other modern AI capabilities to improve business processes and user experiences.
Collaborate with Product Management, Data Science, Engineering, and business stakeholders to translate functional requirements into scalable technical solutions.
Implement high-quality, maintainable, and secure software following established software engineering, AI development, and coding standards.
Contribute to AI model integration, prompt engineering, model evaluation, testing, monitoring, and deployment activities.
Participate in software architecture discussions, design reviews, code reviews, and technical planning sessions.
Troubleshoot, analyze, and resolve moderately complex software, AI, integration, and platform issues.
Develop automated tests, CI/CD pipelines, and deployment processes to improve software quality and delivery efficiency.
Evaluate new AI frameworks, libraries, cloud services, and engineering tools to improve development productivity and product capabilities.
Contribute to technical documentation, design specifications, user training, knowledge sharing, and engineering best practices.
Partner with Quality, Regulatory, Security, Privacy, and Compliance teams to support secure, reliable, and compliant software development.
Support production operations, incident response, defect resolution, and continuous improvement initiatives.
Participating in cross-functional AI and software engineering initiatives.
Learning and adopting emerging AI technologies, software frameworks, and engineering practices.
Supporting enterprise modernization and automation initiatives.
Contributing to special projects or temporary assignments as needed.