AI Program Manager Jobs

AI Chopping Block, Inc.; San Francisco (CA); On-site; USD 150,000 - 200,000; Full time

Job summary

A leading AI technology firm in New York is seeking a Head of EPD Systems and AI Transformation to lead the strategic transformation of Engineering, Product, and Design. You will define and deliver a comprehensive roadmap leveraging automation and AI workflows, while building a team responsible for innovative EPD systems. The ideal candidate will possess strong leadership skills and a technical background, ensuring seamless integration between AI-driven applications and core business processes. This role offers significant responsibility and the chance to drive impactful organizational change.

Qualifications

• Proven ability to lead teams in AI and engineering.
• Experience in transforming engineering processes through automation.
• Strong knowledge of API and microservice architecture.

Responsibilities

• Define and deliver a multi-quarter roadmap for AI transformation.
• Build AI-native EPD operating systems to enhance team workflows.
• Develop tools for monitoring and optimizing AI features across the organization.

Skills

Team leadership

AI workflows

API development

Data optimization

Education

Relevant technical degree

Tools

Cloud-based AI models

Microservices

Job description

Head of EPD Systems and AI Transformation

As Head of EPD Systems & AI Transformation at Vanta, you will lead a strategic transformation and team development by defining, leading, and delivering a multi‑quarter roadmap to transform Engineering, Product, and Design through automation and AI workflows, growing a small team responsible for EPD systems, programs, and the agentic transformation, and serving as a strategic partner to the CPO and EPD Leadership Team by identifying systemic risks and opportunities and implementing interventions. You will design and build an AI‑native EPD operating system that encompasses end‑to‑end information flow across core systems to minimize time spent reconciling data, automate status reporting with team and executive rollups, develop agents that help teams retrieve answers, produce drafts, trigger workflow actions, and maintain data hygiene, and establish continuous evaluation and improvement practices including defining success metrics, running phased rollouts, and measuring adoption. Additionally, you will transform customer and GTM feedback loops by automating ingestion and synthesis of feedback at scale, partnering closely with GTM teams to ensure feedback is actionable and complete the communication loop with customers, and create guardrails for AI‑enabled workflows addressing privacy, data handling, reliability, auditability, and human‑in‑the‑loop expectations in partnership with Security and IT.

Contribute to design, build, and maintain services that power AI‑driven applications, ensuring scalability and performance. Develop APIs and microservices that facilitate seamless integration between cloud‑based AI models and edge devices. Optimize data pipelines and storage solutions for real‑time AI inference and processing. Work closely with AI researchers, infrastructure engineers, and frontend developers to deliver end‑to‑end AI‑driven solutions. Build and optimize an agent orchestration runtime that enables tool use, memory management, and multi‑step reasoning across LLMs, APIs, and edge‑connected systems. Support the implementation of security and privacy best practices for distributed AI systems.

Own the observability and lifecycle management of AI features across the organization. Build tools and infrastructure to enable teams to develop, monitor, and optimize LLM‑powered features. Design and implement closed‑loop evaluation pipelines that automatically validate prompt changes. Develop comprehensive metrics and dashboards to track LLM usage, including cost per feature, token patterns, and latency. Create systems that connect user feedback to specific prompts and LLM calls. Establish best practices and processes for the full lifecycle of prompts: development, testing, deployment, and monitoring. Collaborate with engineering teams across the organization to ensure they have the tools and visibility needed to build high‑quality AI features.

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