Head of AI & Machine Learning

Pivotal Solutions; San Francisco (CA); On-site; USD 220,000 - 360,000; Full time

Job summary

Pivotal Solutions is seeking a Head of AI & AI/ML to lead transformative AI system development. You will guide multi-agent architectures, design custom AI capabilities, and ensure transparent, compliant AI solutions across products.

You will work closely with leadership, engineering, and design teams to push the boundaries of generative AI, enable continuous learning from user feedback, and deliver measurable performance improvements.

Qualifications

• PhD in Computer Science, ML, AI, or related field (required).
• 5+ years in AI/ML R&D, preferably at leading labs or tech firms.
• Expertise with LLMs, multi-agent systems, and AI orchestration.
• Experience applying AI to high-stakes domains (finance/regulated) is valued.
• Proven ability to design agent-based systems for complex tasks.
• Demonstrated success building practical, explainable AI apps.
• Proficiency in retrieval-augmented generation for knowledge‑intense apps.
• Strong understanding of domain-specific data and decision processes.
• Background in human-AI interaction and XAI methodologies.
• Experience learning from user feedback to improve models.

Responsibilities

• Lead the development and scaling of a multi-agent AI platform delivering end-to-end solutions.
• Enhance integration with foundation models while building custom AI capabilities.
• Design and expand agent workflows for complex tasks and decision-making.
• Develop neural architectures optimized for domain-specific reasoning.
• Create purpose-built AI agents with capabilities beyond general models.
• Engineer orchestration layers enabling collaboration among AI agents.
• Build systems to extract insights from diverse data sources (docs, market signals).
• Design evaluation frameworks for performance, trust, and qualitative outcomes.
• Implement loops for continuous knowledge accumulation from user interactions.
• Create explainable AI decision pathways ensuring transparency and compliance.
• Architect interfaces that evolve based on user behavior and preferences.
• Design privacy-preserving AI systems enabling personalization.
• Implement regulatory guardrails to ensure industry standards alignment.
• Collaborate with leadership and teams to integrate AI into products.
• Stay at the forefront of AI innovation with breakthroughs.

Skills

LLMs

Multi-agent systems

AI orchestration

Retrieval-augmented generation

Domain adaptation

Leadership

Python

Education

PhD in Computer Science / ML / AI

Tools

TensorFlow

PyTorch

Hugging Face

Job description

San Francisco, United States | Posted on 09/02/2026

As the Head of AI & Machine Learning, you will lead the development of transformative AI systems, leveraging generative AI and multi-agent architectures to deliver innovative solutions. Your work will focus on creating advanced, custom AI models that process complex, multi-modal data and provide actionable insights. Internally, you will enhance operational efficiency through AI-driven systems. Externally, you will redefine user experiences by delivering personalized, transparent, and accessible AI solutions.

Responsibilities

Lead the development and scaling of a multi-agent AI platform to deliver sophisticated, end-to-end solutions.

Enhance integration with foundation models while building custom AI capabilities tailored to specific needs.

Design and expand agent workflows to handle complex tasks and decision-making processes.

Develop specialized neural architectures optimized for domain-specific reasoning and decision-making.

Create purpose-built AI agents with capabilities beyond general-purpose models.

Engineer proprietary orchestration layers to enable seamless collaboration among AI agents.

Build advanced systems to extract insights from diverse data sources, including documents, market signals, and user inputs.

Design novel evaluation frameworks to measure performance, trust, and qualitative outcomes.

Implement intelligence loops to enable continuous knowledge accumulation from user interactions.

Create explainable AI decision pathways to ensure transparency for users and compliance with regulations.

Architect adaptive interfaces that evolve based on user behavior and preferences.

Design privacy-preserving AI systems to protect sensitive data while enabling personalization.

Implement regulatory compliance guardrails to ensure adherence to industry standards.

Collaborate with leadership, engineering, operations, and design teams to integrate AI systems into products.

Stay at the forefront of AI innovation, researching and applying breakthrough techniques.

Qualifications

PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.

5+ years of experience in AI/ML research and development, preferably at leading AI labs or technology companies.

Expertise in large language models (LLMs), multi-agent systems, and AI orchestration.

Experience applying AI in high-stakes domains, such as finance or regulated industries, is highly valued.

Proven ability to design and implement agent-based systems for complex, real-world tasks.

Demonstrated success in building practical AI applications with transparency and explainability.

Proficiency in retrieval-augmented generation for knowledge-intensive applications.

Strong understanding of domain-specific data and decision-making processes.

Background in human-AI interaction design and explainable AI methodologies.

Experience building systems that learn from user feedback and improve over time.

Deep knowledge of privacy-preserving AI techniques for sensitive data.

Ability to translate business needs into robust AI architectures.

Expertise in balancing innovation with regulatory and compliance requirements.

Strong leadership and mentoring skills with experience guiding technical teams.

Excellent communication skills to collaborate with non-technical stakeholders.

Commitment to building accurate, reliable, and trustworthy AI systems.

Published research in AI/ML conferences or proven industry implementations.

Proficiency in Python and relevant ML frameworks and libraries (e.g., TensorFlow, PyTorch, Hugging Face).