GRAIL
Forward Deployed Engineer - Software Development Engineer – Artificial Intelligence (AI) - #4883
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.
Please note, we have two internal roles open
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. Adaptability and Growth Expectation
- 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.
As our organization continues to evolve and grow, this role may require flexibility in responsibilities and duties. Employees should expect that their role may expand, shift, or be modified to meet changing business needs, strategic priorities, and organizational objectives.
This may include:
These job duties summarize the primary responsibilities of the position and are not intended to be a comprehensive listing of all duties. Responsibilities may change based on business needs.
Required Qualifications
- 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.
- 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.
- 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.
- Experience working in healthcare, biotechnology, diagnostics, life sciences, or regulated environments is preferred.
- Cybersecurity fundamentals and secure software development practices
- HIPAA and protection of sensitive data
- FDA-regulated software environments, software validation, and data integrity principles (preferred)
- 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.
Working knowledge of applicable security, privacy, and regulatory requirements relevant to software development, including:
Working Conditions
- Standard office or hybrid work environment depending on company policy.
- Frequent use of software development environments, AI/ML frameworks, cloud platforms, collaboration tools, and engineering systems.
- May occasionally support production incidents, software releases, or project deadlines outside normal business hours.
- Works independently on assigned projects while receiving guidance and technical direction from senior engineers and engineering leadership.
The expected, full-time, annual base pay scale for this position is $99-121k in Menlo Park, CA and $86K-$105K in Durham NC.
GRAIL Menlo Park, California, USA Office
GRAIL is headquartered in Menlo Park, California, with locations in Washington, D.C., North Carolina, and the United Kingdom. We also have a number of employees who are working remotely. Our bay area office has a employees working in our labs, software engineering, clinical development and more.
Similar Jobs at GRAIL
.png)
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
