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Deffai
Actively Hiring
AI for FDA approvals - predict FDA approvals and get medicine to market faster
  • Top 1% of responders
    Deffai is in the top 1% of companies in terms of response time to applications
  • Responds within a day
    Based on past data, Deffai usually responds to incoming applications within a day

Founding Applied AI / Full-stack Engineer - Agentic Applications

Posted: 5 days ago• Recruiter recently active
Remote Work Policy

Onsite or remote

Visa Sponsorship

Not Available

Preferred Timezones
Pacific Time, Eastern Time
RelocationAllowed
Skills
Python
SQL
Databases
Knowledge Management
API
Benchmarking
Data Annotation
React.js
Model Evaluation
Machine Learning Data Science Python
Agentic Workflow
Multiagent Systems
Agentic RAG
RAGs, ChatGPT, Hugging Face, LangChain, LlamaIndex, Transformers, VectorDB

About the job

About the role

This is a rare opportunity for a hands-on builder to work across the full product stack, build 0 to 1 and grow with a young team. We're looking for a Founding AI / Full-stack Engineer who is passionate about solving challenging problems in a highly regulated industry. You don't have to know FDA or biotech, but you believe in vertical AI solutions and want to push the boundary of what is possible.

Backed by top-tier investors from Applied AI and infra, with advisors from GitHub, OpenAI, and Mercor.

You get market standard comp, equity, viable path to Head of Engineering or beyond.

You will work closely with 2 engineers on the team, build, ship quickly and shape our product vision.

You'll work on the full production pipeline including data pipeline, database, RAG, multi-agent orchestration, eval benchmarks for internal agent performance and frontier model benchmarking.

You'll work with diverse data sources and cross-domain with experts to translate domain knowledge into structured databases.

Key Responsibilities

  1. Build & Ship: Own architectural decisions that balance innovation, scalability, cost, and long-term maintainability in a high-stakes domain.
  2. Ingest at Scale: Build robust, scalable pipelines to ingest, extract, and structure heterogeneous regulatory sources into training- and retrieval-ready datasets.
  3. Data Quality: Ensure data quality, provenance, versioning, and governance across the corpus, with automated validation and monitoring.
  4. Benchmark & Evals: Build datasets, define rigorous metrics, and measure model performance across high-impact AI tasks to guide development.
  5. Human Annotations: Build scalable pipelines to collect structured human feedback, benchmark subjective quality, and inform model iterations.
  6. Collaborating with former FDA experts to accelerate their regulatory review workflows.
  7. Improving RAG, citations, agent tool use, and memory across complex documents.

Day to day, you’ll

  1. Build backend and frontend features using AI coding tools.
  2. Debug agent workflows and improve quality, latency, and cost.
  3. Turn expert feedback into product improvements and evaluations.
  4. Fix a retrieval, citation, or tool-use issue in an existing workflow.
  5. Add an evaluation case, measure the improvement, and ship the fix.

Requirements

  1. Familiarity with Python or TypeScript
  2. Working knowledge of APIs, SQL, Git, and testing
  3. Experience with LLM applications, tool calling, or RAG
  4. Able to build, debug, and test applications using AI coding tools
  5. Able to learn quickly and own features from idea to delivery

Nice to have

  1. Experience with agent workflows, evaluations, or tracing
  2. Familiarity with FDA regulatory workflows or scientific literature
  3. Healthcare, life sciences, biomedical, or FDA-related experience
  4. Experience with React, FastAPI, PostgreSQL, AWS, or agent evaluation tools
  5. Background or project experience in healthcare, life sciences, or biomedical engineering

Who you are

  1. Cracked: You love to build.
  2. Strong opinions: You have strong opinions and product taste, and you're not afraid of pushing back.
  3. Real-World Experience: You have experience building data pipelines, ML infrastructure, and have shipped products in previous startups or projects.
  4. Execution-Oriented: You move fast, take ownership, and focus on solving real problems.
  5. Clear Communicator & Team Player: You collaborate well across functions and push decisions forward.

Interview process

  1. 30min intro with CEO & cofounder
  2. 40min tech call where you meet our engineering team
  3. Short paid take-home (~5hr) for mutual evaluation

Decision in 2 weeks. Don't miss this rare opportunity to define the next generation of medicine approvals.

We hope to hear from you.

About the company

Deffai company logo

Deffai

Actively Hiring
AI for FDA approvals - predict FDA approvals and get medicine to market faster1-10 Employees
  • Top 1% of responders
    Deffai is in the top 1% of companies in terms of response time to applications
  • Responds within a day
    Based on past data, Deffai usually responds to incoming applications within a day
Learn more about Deffai image

Funding

AMOUNT RAISED
Undisclosed amount
FUNDED OVER
1 round
Round
PRE
Undisclosed amount
Pre-Seed - Jan 2026

Founders

Liz Wang
CEO • 1 year
San Francisco Bay Area
image
View the team image

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