Senior AI Engineer (San Francisco)

About Woebot Health

Were a mission-driven startup reinventing the way people find moments of care, clarity, and support through digital experiences. Our team blends engineering, design, and product minds with a shared passion for building human-centered technology. Using the latest advances in language models, real-time interactions, and conversational design, were creating a next-generation digital companion that helps people feel seen, supported, and empowered - wherever they are, whenever they need it. With backing from top-tier investors and a bold vision for the future, were moving fast, learning constantly, and designing for real-world impact at scale.

We believe the future of generative AI lies not in novelty, but in precision, nuance, and emotional resonance. If youre driven by solving hard problems in applied AI and want to shape systems that genuinely serve people, wed love to meet you.

Why Join Us?

Our founding team includes legendary AI pioneer Andrew Ng, co-founder of Coursera, founder of deeplearning.ai , former head of Google Brain, and the driving force behind AI courses that have educated millions worldwide. Andrews active involvement as a co-founder and board member offers a rare opportunity to collaborate closely with one of the most influential minds in artificial intelligence.

Working from the dynamic AI Fund offices, youll have direct access to mentorship, innovative resources, and a vibrant community of technologists shaping the forefront of AI. Join us to build cutting-edge solutions, advance your skills rapidly, and make a tangible difference alongside industry visionaries committed to precision, nuance, and human-centric innovation.

The Role

Were hiring a Senior AI Engineer to help architect and evolve the cognitive engine of our companion platform. This role sits at the intersection of model tuning, inference optimization, and intelligent orchestration, focused on building adaptive systems that can shift modes fluidly depending on user needs.

Youll partner closely with our psychology, product, and infrastructure teams to :

Lead fine-tuning of foundational models using efficient training techniques and custom datasets

Design and implement model orchestration logic that determines when to retrieve, route, generate, or escalate across different conversational contexts

Build and iterate on eval frameworks for long-form, multi-turn interactions - prioritizing emotional coherence and user outcomes over token accuracy

Stay on top of rapid developments in LLMs, fine-tuning frameworks, and inference efficiency, translating that knowledge into action

Champion best practices for scaling training workflows, experimenting safely, and continuously learning from real-world feedback

This is a hybrid position, with 2-3 days per week in San Francisco or Mountain View.

What Youll Do

As a Senior AI Engineer, you will be responsible for architecting, optimizing, and evolving the cognitive engine of our AI companion. Your work will combine deep model training expertise with real-world experimentation, striking a balance between precision, nuance, and adaptability. Youll collaborate across AI, product, and design to translate emotional and behavioral intent into reliable, scalable machine intelligence.

Your Focus :

Prompt Engineering & Optimization

Design, iterate, and evaluate prompt strategies for complex multi-turn interactions using frameworks like DSPy

Build prompt libraries and A / B test variants to optimize for safety, clarity, and on-brand responsiveness

Leverage prompt engineering as a short-term strategy where fine-tuning is not yet appropriate, with a clear view on trade-offs

Agentic Reasoning & Orchestration

Evaluate and integrate modular orchestration strategies (e.g., LangGraph, LlamaIndex, Letta, PydanticAI), forming a perspective on their relevance and scalability

Design systems that can switch between reflection, coaching, or directive states based on context, using either routing logic or learned behavior

Collaborate with the product team to define how tools, memory, and reasoning modules interact without overcomplicating the user experience

Model Fine-Tuning & Optimization

Own parameter-efficient fine-tuning pipelines (e.g., LoRA, QLoRA) to adapt foundational models to brand-specific voice, tone, and emotional range

Curate high-quality datasets and design eval metrics tailored to coherence, empathy, and state consistency across sessions

Explore model compression, quantization, and inference optimization for low-latency voice and mobile interactions

Experimental Thinking & Evaluation

Design lightweight experiments to validate technical approaches and measure outcomes beyond accuracy (e.g., trust, emotional congruence)

Partner with domain experts to implement human-in-the-loop annotation systems where automation falls short

Ship prototypes and production features rapidly, with a build-learn-refine approach

What Were Looking For

Deep Technical Fluency

5+ years in AI / ML engineering, with at least 2 years of hands-on fine-tuning large language models

Strong understanding of the trade-offs between fine-tuning, tool invocation, prompt orchestration, and hybrid approaches

Proficiency with model training workflows, scalable data pipelines, and LLM evaluation techniques

Practical experience with low-latency inference environments and model optimization strategies (quantization, compression, routing logic)

Comfortable in Python and modern ML tooling; experienced deploying models to production environments

Product-Oriented Thinker

Ability to translate product or psychological intent into model architecture or training strategy

Experimental mindset with a bias toward measurable learning and iterative improvement

Strong communicator who can explain the why behind the how to technical and non-technical partners alike

Demonstrated curiosity for emerging methods and a track record of staying current on deep learning advancements

Collaborative, Bold & Humble

Team-first engineer who values listening as much as leading

Comfortable with challenging ideas while seeking the best solution, not credit

Motivated by impact and aligned to our mission of building AI that helps people

Bonus if You Have

Experience at AI-first companies

Knowledge of conversational state management, memory systems, or emotional alignment in LLMs

Exposure to orchestrated AI frameworks or modular agentic architectures

What We Offer

Compensation : $180,000 - $225,000 base + equity

Benefits : Medical, dental, vision for you and your family

Time Off : Flexible PTO and mental wellness support

Learning Stipend : Annual budget for courses, conferences, or certifications

Remote Support : One-time home office setup stipend

Security : Company-sponsored life and disability insurance + 401(k)

We are committed to fostering an inclusive and equitable workplace. Compensation decisions are based on a variety of factors, including location, skills, experience, and various market benchmarks.