Senior/Staff Full Stack Engineer

Job Description

Job Description

Career Renew is recruiting for one of its clients a Senior/Staff Full Stack Engineer - this is an onsite role in San Francisco. Salary range: 175-270K USD base plus benefits plus equity.

The scientific decision engine for R&D. Raw data → defensible decisions, faster.

Pharma and biotech R&D often spend weeks, or even months, learning, coding, and troubleshooting discovery analysis pipelines. This slows research and diverts focus from the work that truly matters: discovery.

We change that. Using only natural language from the user, our AI builds custom workflows with full transparency and reproducibility for discovery data (omics and beyond), on-demand and in minutes, not weeks. Discovery researchers across therapeutic areas can instantly align, analyze, interpret, integrate, and iterate hypotheses for complex datasets without manual coding or repetitive setup.

By automating these time-consuming processes, we empower scientists to spend more time designing experiments, testing insights, and driving high-quality discoveries, including novel IP. From accelerating data analysis to uncovering novel targets and biomarkers, we are the Scientific Decision Engine that turns data into actionable breakthroughs.

We're are looking for a Senior/Staff Full Stack Engineer with 4+ YOE to join our Engineering team. We need a builder who is excited to create foundational systems and have meaningful influence on our technology as we work to accelerate drug discovery and improve human health globally. This is a top priority hire driven by our hypergrowth and the need to scale our core product to meet surging enterprise demand.

Responsibilities

• Build new product features and systems from scratch across frontend and backend, directly expanding Mithril's platform capabilities for world-class researchers

• Design, build, and own scalable backend services, APIs, and data pipelines that power the Mithril AI platform across the application, identity, data storage, and ML layers

• Work within fast-moving sprint cycles to ship code quickly, contributing to production within your first few weeks

• Collaborate with a cross-functional team of engineers, product managers, designers, and AI scientists to translate complex scientific workflows into intuitive, high-performance software

• Own features end-to-end from early development through production deployment, iteration, and scale — ensuring they deliver real value to researchers at leading pharma and biotech organizations

Requirements :

4+ years of experience in professional full-stack or backend engineering (not including internships) (Mandatory)

Built products at early-stage or high-growth startups, preferably as a founder or early employee (Mandatory)

Experience shipping and owning production systems used by real customers (Mandatory)

Experience designing and working with scalable systems, databases, and data-intensive applications.(Mandatory)

BS in Computer Science, STEM, or related technical skill (Mandatory)

Strong proficiency in modern frameworks, like Python and React (Mandatory)

Experience building backend services and REST APIs, with Django as a plus (Mandatory)

Familiarity with GraphQL and cloud infrastructure , like AWS (Nice-to-have)

Intellectually curious and excited to learn – ask questions and engage deeply with the product and problem space (Mandatory)

Positive and collaborative with the energy to thrive in a high-communication, in-person team culture.(Mandatory)

Demonstrated interest in life sciences, drug discovery, or computational biology (Nice-to-have)

Why candidates should join

Why us?

• Real impact: Our platform is used daily by world-class researchers at J&J, Roche, Eli Lilly, AstraZeneca, and Siemens compressing months of drug discovery into minutes.

• Hypergrowth: 12x YoY revenue growth; $0 to $2M in year one, on track to blow past $10M this year — three enterprise deals closed in a single week

• Strong funding: $XXM Series A (~$100M valuation) led by Obvious Ventures, a deep tech and biotech specialist fund; stealth only share details on call (not written)

• Proprietary moat: The biological knowledge graph is core IP — integrating global genomic datasets, published research, and proprietary data into a context layer that OpenAI and Anthropic can't replicate overnight

Why this Role?

• Builder: You're building V1 of a product that enterprise pharma is already paying for — greenfield full stack work with end-to-end ownership from concept to production

• Career accelerator: Engineering grows from 10 to 30 by EOY and 60–70 the year after — tech lead and manager paths are imminent. Create your own adventure in terms of where you want to take your career

• Competitive Comp: $175K–$270K base + 0.3–0.6% equity