Our client, a world
leader in biotechnology and life sciences, is looking for a "Sr AI
Fullstack Engineer” based out of South San Francisco, CA.
Job Duration: Long
Term Contract (Possibility Of Extension)
Pay Rate : $85/hr on W2
DOE
Company Benefits: Medical, Dental,
Vision, Paid Sick leave, 401K
Duration: Long term
contract (Possibility of further extension)
The Sr AI Fullstack
Engineer will primarily be responsible for designing, developing, and deploying
software which interacts with cutting-edge generative AI models and
applications in collaboration with AI scientists, full stack developers, and
others.
The Opportunity:
- Innovate and develop
software applications to support clinical development
- Identify and integrate
AI/LLM capabilities to enhance data processing and natural workflows.
- Design intuitive,
user-centric interfaces.
- Code Quality and
Documentation: Write clean, maintainable, and well-documented code. Participate
in code reviews and contribute to best practices in software development.
- Research and
Innovation: Stay up-to-date with the latest advancements in generative AI and
machine learning. Evaluate new technologies and methodologies to continuously
improve our solutions.
- Collaborate with
Cross-Functional Teams: Work closely with data scientists, engineers, and
product managers to integrate generative AI capabilities into our products and
services.
- Deployment and
Monitoring: Develop and maintain robust deployment pipelines for AI-enhanced
applications. Monitor pipeline performance in production and implement
necessary improvements.
Minimum Requirements:
- Bachelor’s or Master’s
degree in Computer Science, Engineering, Mathematics, or a related field.
- 5+ years of full stack
development experience
- Strong proficiency in
either a front-end framework (Vue.js, React, or similar) and a backend web
frameworks in Python and/or JavaScript (Django, FastAPI, Flask, Next.js, or
similar)
- 4+ years experience
with front-end frameworks (preferably Vue.js)
- 2+ years of developing
and deploying AI/ML solutions or applications
- Experience designing
and developing RESTful APIs (with e.g. Python FastAPI).
- Familiarity with prompt
engineering
- Proficiency with
containerized workflows and architectures (Podman, Docker, Kubernetes)
- Strong automated
software testing skills (Python unittest, jest, Playwright)
- Familiar with Agile
methodologies
- Leading system design
and implementing scalable, fault-tolerant solutions for complex, distributed
computing challenges.
- Experience with cloud
platforms (e.g. AWS) and modern data platforms (e.g., Snowflake).
- Experience implementing
chatbots, retrieval-augmented generation (RAG) systems, and integrating LLMs
into applications (AI-assisted automation)
Preferred
Qualifications:
- Experience building AI
agents, fine-tuning LLM models, and evaluating bias and fairness with LLM
systems
- Experience in
developing Microsoft Word add-ins using Office.js.
- Experience with web
technologies like JWT, WebSockets, etc.
- Experience with
Huggingface, Langchain, TensorFlow, PyTorch, or similar.
- Familiarity with
DevOps, infrastructure, and continuous integration concepts.
- Familiarity with CRDT
technologies like Yjs.
- Experience with using
NLP/LLMs on clinical text.
- Basic knowledge of
clinical drug development
If interested, please
send us your updated resume at
[email protected]/[email protected]
Similar Jobs
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


