Senior AI Engineer

ZipRecruiter; San Francisco (CA); Hybrid; USD 180,000 - 225,000; Full time

Job summary

A leading startup is seeking a Senior AI Engineer to play a crucial role in developing the cognitive engine of an innovative AI companion platform. With a focus on model optimization and context-aware AI systems, you'll collaborate closely with cross-functional teams. Join a mission-driven organization backed by industry pioneers to shape the future of AI technology while benefiting from a competitive compensation package, including equity and flexible work arrangements.

Benefits

Medical, dental, vision benefits

Flexible PTO

Learning stipend for courses and conferences

Home office setup stipend

Company-sponsored life and insurance

401(k)

Qualifications

• 5+ years in AI/ML engineering, with 2+ years in fine-tuning large models.
• Proficiency in Python and modern ML tooling; experienced deploying models to production environments.
• Ability to design systems for contextually adaptive AI behaviors.

Responsibilities

• Architect and evolve the cognitive engine for the AI companion.
• Lead model tuning, design orchestration logic, and build evaluation frameworks.
• Collaborate with teams to translate user needs into scalable AI solutions.

Skills

Model Fine-Tuning

Prompt Engineering

Orchestration Strategies

Data Pipelines

User Experience Design

Tools

DSPy

LoRA

QLoRA

LangGraph

LlamaIndex

Job description

Job DescriptionJob Description

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 models, real-time interactions, and conversational design, we’re creating a next- 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 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 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.