Senior/Staff AI Engineer

AI Talent Now; San Mateo (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

AI Talent Now is seeking experienced professionals to join our AI team to build Lighthouse AI. This role involves collaborating with product and engineering teams to define and integrate features that enhance software delivery systems.

The ideal candidate will have over 5 years of AI and ML engineering experience and a strong background in deploying features in production environments.

Qualifications

• 5+ years of experience with a focus on AI and ML engineering.
• Experience working on enterprise SaaS products.
• Strong in LLM or Agent engineering.

Responsibilities

• Collaborate with product, data, and engineering teams.
• Build and maintain scalable ML pipelines and infrastructure.
• Design and implement prompt engineering strategies.

Skills

AI engineering

ML engineering

Docker

Kubernetes

Natural language processing

Education

Degree in Computer Science, Mathematics, Data Science, or a related field

Tools

ML pipelines

Helm charts

Job description

United States > San Mateo, United States | Posted on 06/19/2026

AI Talent Now, LLC is a powerhouse in direct‑hire talent acquisition, connecting exceptional talent with industry‑leading organizations across IT, Engineering, Financial Services & Fintech, and Manufacturing & Robotics. Headquartered in Atlanta, Georgia, we proudly serve clients and candidates nationwide.

Job Description

AI Talent Now Job # ZR 83

At this exciting AI company, we are reshaping the way engineering organizations operate, with an engineering intelligence platform that provides visibility and context across the organization’s software delivery systems. This deep operational context supports engineering leaders today, and is increasingly essential as AI agents begin to operate within real software delivery environments. We are laying the foundation for how humans and AI will build software together in the years ahead.

About the Role

Join our AI team to build Lighthouse AI – the intelligence engine that helps engineering leaders understand why their teams perform the way they do and improve performance in an age where AI is redefining the engineering craft. You’ll work on natural language interfaces, causal analysis models, and ML‑driven insights that impact how thousands of engineers work at companies like Autodesk, Discord, and Vimeo.

Responsibilities

• Collaborate with product, data, and engineering teams to define, design, and integrate AI features seamlessly into the user experience.
• Build and maintain scalable ML pipelines and infrastructure balancing speed, flexibility, security, and scalability.
• Build and optimize LLM‑powered features including natural language query generation, data summarization, and data exploration tools.
• Design and implement prompt engineering strategies, evaluation frameworks, and iterate on model performance.
• Fine‑tune Large Language Models (LLMs) or custom architectures for performance, latency, and cost‑efficiency.
• Stay up‑to‑date with the latest research (e.g., papers from NeurIPS, ICML) and identify opportunities to apply state‑of‑the‑art techniques to business problems.

What We Value

• Living by our values over avoiding conflicts – We speak honestly, act transparently, and stay true to our principles, especially when it’s difficult.
• Daring to be great over eliminating weaknesses – We win by excelling at what matters most, not by imitating or outdoing competitors.
• Moving fast over perfection – We value learning, iteration, and agility more than waiting for “perfect.”
• Individual responsibility over process – We trust you to own outcomes, make thoughtful decisions, and be accountable for results.

Requirements

• Staff, Principal, or TL level IC
• 5+ years of experience with a focus on AI and ML engineering
• Have built and deployed AI/ML features end‑to‑end in a production environment
• Experience working on enterprise SaaS products
• Experience at an early‑stage startup
• Degree in Computer Science, Mathematics, Data Science, or a related field
• Classical Machine Learning background
• Strong in LLM or Agent engineering – evaluation frameworks, fine‑tuning or custom architectures for latency, cost, performance
• Comfortable with Docker, Kubernetes, Helm charts; can take ML/AI work into production
• Highly independent and self‑directed
• AI‑forward in how they personally work – always using the latest tools