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Head of Engineering

Job in Pleasanton, Alameda County, California, 94566, USA
Listing for: Judge Group, Inc.
Full Time position
Listed on 2026-10-05
Job specializations:
  • Software Development
    Software Architect, Software Project Mgr/ Lead, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 225000 - 265000 USD Yearly USD 225000.00 265000.00 YEAR
Job Description & How to Apply Below

Location: Pleasanton, CA Salary: $ USD Annually – $ USD Annually Description:

Head of Engineering

Location: Hybrid – Pleasanton, CA 94566

Department: Engineering

Reports To: Chief Technology Officer (CTO)

Compensation: 225-265 plus 25% bonus

Our client is transforming the way the global food and perishables supply chain operates. They are rebuilding our engineering organization to be AI-native: smaller, more senior, and dramatically more leveraged. Their mission is to deliver significantly greater output through the intelligent use of AI agents, automation, and exceptional engineering talent.

Engineering is at the center of this transformation. They build the platforms, products, and intelligent agents that unlock efficiency across the entire company and for the customers who depend on us every day.

The Opportunity

They are seeking a Head of Engineering to lead one of our core product domains within our supply chain software platform. In our world, timing, traceability, reliability, and accuracy are not features, they’re the product.

This is a hands-on technical leadership role for an experienced engineering leader who can balance business outcomes, technical excellence, and organizational scale. You will lead a lean, high-performing team responsible for delivering through our AI-powered, agentic software development lifecycle (SDLC), while partnering closely with Product, Security, Operations, and executive leadership.

Reporting directly to the CTO, you will be one of a small number of senior engineering leaders shaping the future of our technology organization.

What You’ll Do

Own a Product Domain End-to-End

  • Take full accountability for architecture, delivery, quality, performance, and business outcomes within your engineering domain.
  • Drive technical strategy and execution aligned with company objectives.
  • Make critical decisions that balance speed, scalability, reliability, and maintainability.

Lead a High-Leverage Engineering Organization

  • Manage and mentor engineering leads, senior full-stack engineers, and high-potential early-career engineers.
  • Coordinate effectively with offshore engineering specialists and distributed teams.
  • Develop future technical leaders and strengthen the overall engineering bench.

Drive Delivery Through an Agentic SDLC

  • Lead teams operating within an AI-enabled software development lifecycle where agents assist with requirements, code generation, testing, reviews, and delivery.
  • Ensure appropriate human oversight and accountability at every stage.
  • Maintain a high quality bar while accelerating delivery speed.

Elevate Engineering Productivity

  • Champion AI-powered development practices that increase per-engineer output and effectiveness.
  • Establish workflows, standards, and operating models that maximize leverage from modern AI tools.
  • Continuously improve engineering metrics such as throughput, cycle time, quality, and operational excellence.

Provide Technical Leadership

  • Own architecture and system design decisions for large-scale, mission-critical applications.
  • Evaluate technical proposals and challenge assumptions when necessary.
  • Guide teams through complex tradeoffs involving scalability, performance, reliability, security, and cost.
  • Contribute directly when needed through architecture reviews, design sessions, prototyping, or technical problem solving.

Ensure Quality, Reliability, and Operational Excellence

  • Build systems that support real-world supply chain operations where outages and inaccuracies can impact inventory, shipments, compliance, and customer trust.
  • Establish strong engineering standards, observability practices, and reliability measures.
  • Drive continuous improvement in system resilience and performance.

Partner Across the Business

  • Collaborate with Product Management, TPMs,…
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