Forward Deployed Scientist (AI Agents | Drug Discovery | Enterprise Biotech) in South San Francisco

Energy Jobline
South San Francisco, CA, United States
22 days ago
Apply on www.energyjobline.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
1 year minimum
Compensation
$190,000.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Bioinformatics Computational Biology

Requirements

We’re looking for AI- scientists who combine deep scientific expertise with startup execution, customer empathy, and a passion for solving real-world problems., PhD (or MD/PhD) in Biology, Chemistry, Pharmacology, Bioinformatics, Computational Biology, or a related discipline, 1-6 years of post-PhD industry (Startup) experience in leading pharmaceutical companies, biotechnology organizations, CROs, or life sciences consulting firms

Benefits & conditions

Operating with a flat organizational structure and a culture built around ownership, speed, innovation, and execution, every team member has the opportunity to shape both the product and the future of AI-powered biomedical discovery.

\n

\n

Why This Role Is Different

\n

Most scientific roles focus on research.

\n

Most AI roles focus on technology.

\n

This role combines science, AI, product, and customer success into one high-impact position.

\n

You’ll work directly with enterprise scientists to understand complex research workflows, deploy AI-powered solutions, improve AI agent capabilities, and influence product direction through real customer feedback.

\n

\n

You’ll think like a scientist, communicate like a consultant, and execute like a product builder.

\n

You’ll have the opportunity to:

\n

Design AI-powered scientific workflows

\n

Partner with leading pharmaceutical and biotech organizations

\n

Improve next- biomedical AI agents

\n

Drive enterprise adoption of AI products

\n

Influence product strategy through customer insights

\n

Help shape the future of AI-powered drug discovery.

\n

\n

What You’ll Be Building

\n

You’ll help develop the intelligence powering AI agents across the drug R&D pipeline.

\n

Your work will include:

\n

Designing scientifically rigorous AI workflows for drug discovery and development

\n

Collaborating directly with enterprise scientists to solve complex research problems

\n

Building biomedical skills, tools, and data integrations that improve AI agent performance

\n

Developing evaluation frameworks that ensure scientific quality, reliability, and accuracy

\n

Delivering customer workshops, scientific training sessions, and product enablement

\n

Working closely with Product and Engineering teams to transform customer feedback into new capabilities

\n

Every solution you build will directly influence how leading pharmaceutical organizations leverage AI to accelerate biomedical innovation.

\n

\n, n \n

  • Drug Discovery \n

  • IND-Enabling \n

  • Clinical & Translational Research \n

\n

An AI- mindset, actively using LLMs and AI tools to accelerate scientific workflows

\n

Strong customer-facing experience, including scientific consulting, stakeholder engagement, solution design, workshops, or training delivery

\n

Practical coding skills (Python ) with familiarity in GitHub and cloud environments

\n

Startup experience is mandatory .

\n

\n

Tech stack

\n

Python, ChEMBL, PubChem, RFdiffusion, ProteinMPNN, ESM, Simcyp, GastroPlus, NONMEM, LLMs / AI Agents, Genomic Foundation Models, Protein Models, CDISC, EHR/Claims Data, GitHub, AWS

\n

Who Isn’t the Right Fit?

\n

This role is intentionally selective.

\n

It is not designed for candidates who:

\n

Have purely academic backgrounds without meaningful industry experience

\n

Focus exclusively on mechanistic biology or early-stage target discovery

\n

Lack customer-facing or stakeholder engagement experience

\n

Have worked only in large, process-heavy organizations and are uncomfortable with startup pace and ownership

\n

Prefer management responsibilities over hands-on scientific execution

\n

Don’t actively leverage AI in their daily work

\n

Have no practical coding capability

\n

\n

The team values scientific excellence, adaptability, ownership, customer obsession, and execution speed equally.

\n

\n

About the company

The future of biomedical discovery won’t be driven solely by breakthroughs in AI-it will be driven by scientists who can successfully deploy AI into real-world research environments., n

Join a venture-backed AI startup building the next of agentic intelligence for biomedical discovery.

\n

Founded by pioneering researchers in AI and computational biology, the company is developing intelligent AI agents capable of understanding, reasoning through, and executing complex biomedical workflows across the drug development lifecycle.

\n

Already trusted by approximately 20 enterprise customers, including several of the world’s largest pharmaceutical and biotechnology organizations, the platform is helping accelerate scientific discovery through production-ready AI solutions.

\n

Backed by $13.5M in seed funding from leading venture capital firms and guided by world-renowned scientists and AI pioneers, the company combines world-class research with real commercial impact.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.energyjobline.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:47 min

Expanding AI agents across workflows and team structures

Brian Scanlan Brian Scanlan · World Congress 2026 Europe

54 sec

Detecting smart devices and experimenting with biological computing networks

Chris Heilmann +2 · LIVE

3:46 min

Core terminology and audiences for interpretable artificial intelligence

Karol Przystalski · LIVE

1:19 min

Empowering life science researchers with artificial intelligence

Jeremy Murray Jeremy Murray · World Congress 2026 Europe

5:42 min

Evaluating bizarre tech headlines in fake or news segment

Chris Heilmann +2 · LIVE

3:21 min

Automating complete quality assurance pipelines with artificial intelligence

Evelyn Haslinger · LIVE

Videos

See all

Related articles

See all