Osanni Bio is a development-stage therapeutics platform, headquartered in San Francisco, California. We are creative and agile innovators, relentlessly curious about finding new ways to target the biology behind diseases with the greatest unmet need and determined to do something about it.
At the center of Osanni is its innovation engine, which is optimized for discovering new scientific insights, designing novel drug concepts, and efficiently advancing programs to a meaningful proof-of-concept. Once a program is sufficiently de-risked, it graduates into its ecosystem of affiliate companies, which are equipped with the dedicated focus, specialized talent and support necessary to scale. Osanni's architecture marries the scientific depth and operational power of a centralized platform with the speed, agility and accountability of independent companies. The result: an opportunity to create and deliver more transformative medicines.
We hold patients and the physicians who care for them as our North Star. It guides our purpose, sharpens our decision-making, and defines our impact.Osanni is currently advancing programs in ophthalmology, cardiology and beyond. We are building a highly skilled team, passionate about having an impact on human health. Be part of creating an organization where people enjoy their work and their colleagues, are valued for their individuality, and can't imagine working anywhere else.
Our Values:
Osanni is guided by three core values: Integrity + Impact, because we give a hoot; Agility + Accountability, so we swoop and soar; and Collaboration + Connection, to be one Osanni Flock. Together, they shape how our team shows up for patients, for each other, and for the mission.
About the Role:
Osanni is investing in internal AI infrastructure to accelerate how the company discovers and validates scientific insight, from organizing internal knowledge to supporting more sophisticated, automated research workflows. We're looking for a hands-on Applied AI Engineer to design, build, and maintain the systems that power this capability as a member of a newly forming team within Discovery Innovation.
This is a founding infrastructure role. You'll bring significant technical ownership and latitude to shape the architecture from the ground up, working closely with the Senior Director, Discovery Innovation and collaborating with other team members as the group grows, while partnering broadly across the organization, spanning science, business operations, legal, and beyond, to build internal tools that advance efforts across every function. As the group scales, there's real room to grow with it. This role is based out of our San Francisco Bay Area headquarters (hybrid, on-site required).
What You Will Do:
- Design and build backend infrastructure for internal AI knowledge systems, including how information is structured, stored, and kept consistent and current as it grows.
- Architect the data layer for these systems, with real influence over the approach, whether graph-based, vector-based, hybrid, or emerging methods.
- Build infrastructure to support automated, multi-step research and reasoning workflows across distributed components.
- Establish strong data logging and provenance practices so system outputs and decisions remain traceable over time.
- Track the fast-evolving landscape of models, architectures, and orchestration approaches, and bring relevant advances into the systems you build.
- Architect with a future migration path in mind, moving from cloud infrastructure toward a more isolated, private deployment environment.
- Partner closely with the Senior Director, Discovery Innovation and collaborate with fellow members of the newly forming Discovery Innovation team to translate research direction into working technical systems.
- Engage broadly across the organization, including science, business operations, and legal, to understand needs and deliver internal tools that advance efforts across every function.
- Manage multiple priorities in a fast-paced, evolving environment, ensuring deliverables are completed accurately and on time, while performing other related duties as required.
What You Bring:
- Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent hands-on experience.
- 2 to 4 years of professional software engineering experience, or equivalent demonstrated depth through independent projects, open source work, or self-directed building in the LLM/AI space; years of tenure matter less here than evidence of genuine, hands-on depth.
- Hands-on working experience with modern agentic coding platforms (e.g., Claude Code, Codex, Cursor, or similar); this is a baseline expectation, not a nice-to-have.
- A track record of building AI tools, for example having shipped real systems involving LLMs, RAG, or agents on your own initiative.
- Cloud infrastructure experience (AWS, GCP, or Azure).
- Comfort with ambiguity and a builder's mentality; you'll be given a strong vision and real ownership over how it's built.
- Strong communication skills and the ability to work effectively as an early, foundational hire.
- Based in or willing to relocate to the Bay Area; able to work on-site/hybrid.
The expected base pay range for this position is $235,000 - $255,000 plus bonus and comprehensive benefits. The base pay range reflects the target range for this position, but individual pay will be determined by additional factors such as job-related skills, experience and relevant education or training.
We are committed to creating a diverse environment and are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
We will provide an intellectually stimulating, collegial and fast-paced environment. If you are ready to be a part of building the future of transformative medicines, then we are excited to hear from you!
#J-18808-LjbffrPrincipal Applied AI Engineer in san francisco at Unknown Company
This position is listed as full time and hybrid.