Director of Engineering, Agentic Workflows

Red Ventures Home helps partners across the home services ecosystem—telecom, security, energy, and home automation—drive sustainable growth through proprietary distribution, advanced data models, and AI-enabled digital solutions.

We're seeking a Director of Engineering to lead our Central AI Engineering team. This role is focused on transforming how we deliver software —driving adoption of agentic workflows, accelerators, and AI-first engineering practices that fundamentally change delivery speed, quality, and team effectiveness across our organization.

You'll lead an internal platform team whose primary customers are our client delivery teams. You own both the systems that enable delivery and the adoption that makes them successful. This requires technical depth, people leadership, influential communication, and the ability to build compelling investment cases for technology initiatives across a matrixed organization.

The ideal candidate is intellectually curious and continuously experimenting with new AI capabilities, often building side prototypes or exploring emerging tools to understand what is possible.

Curious how Home fits into Red Ventures? Click here .

What You’ll Do:

Transform Delivery Through Agentic Workflows

Lead adoption of agentic workflows and AI-first delivery models across client delivery teams

Build shared services, accelerators, and reusable patterns that materially reduce delivery timelines

Measure and continuously improve delivery efficiency, quality, and consistency

Ensure agentic systems are reliable, maintainable, and applied with clear leverage

Define and scale AI-assisted development practices (Cursor, Windsurf, agent frameworks)

Partner closely with delivery teams to understand friction points and build solutions that drive adoption

Build Investment Cases Drive Strategic Alignment

Develop compelling business cases for technology investments in agentic systems and AI infrastructure

Quantify impact through metrics like delivery time reduction, quality improvements, and team velocity gains

Communicate technical strategy and ROI to senior leadership and stakeholders

Influence resource allocation and prioritization across competing initiatives

Translate technical capabilities into business value that resonates with non-technical audiences

Provide Technical Architectural Leadership

Set architectural direction for agentic systems, accelerators, and shared AI services

Ensure systems are modular, secure, observable, and production-ready

Uphold strong engineering discipline while balancing innovation and pragmatism

Provide hands-on guidance to Senior and Staff engineers when needed

Define standards across Python, JavaScript/TypeScript, testing, CI/CD, and MLOps

Build and Scale the Team

Hire, develop, and retain AI engineers

Set clear expectations, career paths, and growth plans

Foster a culture of accountability, curiosity, experimentation, and delivery

Coach teams to operate effectively in ambiguous, fast-moving environments

Build a team that thinks like internal entrepreneurs; focused on customer (delivery team) adoption and impact

Lead Cross-Functionally

Act as a trusted partner to delivery teams, Product, Design, and Data leadership

Translate business strategy into executable technical plans

Communicate tradeoffs, progress, and impact to senior leaders with clarity and conviction

Influence effectively in a matrixed organization where adoption matters as much as technical execution

Build coalitions and drive alignment across stakeholders with competing priorities

What We’re Looking For:

10+ years of engineering experience, including leadership of high-performing teams

Experience building and operating production AI, ML, or data-driven systems

Strong software architecture and technical judgment

Track record of improving delivery velocity and engineering maturity through platform or tooling investments

Proven ability to build investment cases and secure buy-in for technology initiatives

Strong influential communication skills—ability to communicate technical concepts to both technical and non-technical audiences

Experience with modern AI stacks, including LLMs, agent frameworks (LangChain, LangGraph), and ML platforms

Demonstrated hands-on experience building with modern AI technologies (LLMs, agents, RAG systems, evaluation frameworks, etc.) through production systems, prototypes, or personal experimentation.

Strong Python experience; familiarity with JavaScript and TypeScript

Experience with Databricks, MLflow, and modern data platforms

Understanding of traditional ML and how it complements generative AI

Compensation:

This range reflects total cash compensation, which may include base salary only or base salary plus target bonus, depending on the role. Where eligible, equity may also be offered separately and not included below. Actual compensation varies based on location, experience, and qualifications.

Total Cash Compensation Range…