About Woebot Health
We’re 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, we’re 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, we’re 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 you’re driven by solving hard problems in applied AI and want to shape systems that genuinely serve people, we’d 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. Andrew’s 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, you’ll 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
We’re 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.
You’ll 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 You’ll 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. You’ll 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 We’re 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.
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Founded in 2017 by Dr. Alison Darcy, Woebot is the mental health ally that’s by your side for whatever’s ahead. From a small tech experiment alleviating anxiety in teens, Woebot Health has grown into an emerging force of change in mental health.
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