Director, Engineering, Agentic Content

Avalara•UNAVAILABLE, UNAVAILABLE

About The Position

Avalara is building the Agentic Content Studio Platform (ACSP), a next-generation platform designed to improve how global tax and compliance content is sourced, maintained, validated, and consumed across the business. The Director of Engineering, Agentic Content Engineering, will lead the strategy, architecture, and execution of Agentic Content Studio Platform. This platform will support expansion into new content domains including VAT Advanced Sections, Registration, Business Licenses, XBorder Marketplace, and Communications, while also improving the efficiency and scalability of existing content operations through automation and AI-assisted workflows. This role combines platform engineering, applied AI, workflow automation, and organizational leadership. Success in this role requires balancing technical innovation with operational rigor, measurable business outcomes, platform reliability, and responsible AI adoption. The platform is expected to improve content scalability, accelerate onboarding of new content domains, reduce manual research effort, and enable content teams to operate through AI-assisted and human-reviewed workflows.

Requirements

Bachelor’s degree in Computer Science, Engineering, or related field.
12+ years of software engineering experience, including large-scale platforms or distributed systems.
5+ years of experience leading engineering managers and senior engineers in complex cross-functional organizations.
Proven experience leading platform strategy, architecture, and execution with measurable business outcomes.
Experience applying AI and automation to improve operational scale, quality, productivity, or customer impact.
Strong experience with distributed systems, APIs, workflow orchestration, integrations, and event-driven architectures.
Experience building platforms that support automation, operational observability, and human-in-the-loop workflows.
Strong cross-functional leadership skills with the ability to align engineering investments to business priorities.
Excellent execution rigor, technical judgment, communication skills, and organizational leadership.
Experience with LLMs, agent-based systems, RAG architectures, or equivalent AI platforms.
Strong engineering background in Python and modern AI application frameworks.
Experience building cloud-native systems on AWS, Azure, or GCP.
Familiarity with MLOps practices including CI/CD, evaluation pipelines, monitoring, and model lifecycle management.
Strong platform and systems design experience focused on reliability, scalability, and operational excellence.
Demonstrated ability to build and mentor high-performing engineering organizations.
Strong product and platform mindset with a focus on customer and business outcomes.
Ability to communicate effectively with senior technical and executive stakeholders.
Pragmatic, execution-oriented leader capable of operating strategically while remaining technically engaged.

Responsibilities

Define and execute the engineering vision, architecture, and delivery roadmap for the Agentic Content Studio Platform.
Build scalable platform capabilities that support onboarding and maintenance of global compliance content across multiple domains.
Lead development of AI-assisted workflows that automate sourcing, extraction, transformation, validation, and maintenance of content.
Establish reliable human-in-the-loop operating models that combine AI-driven automation with researcher review and oversight.
Design secure, observable, and resilient platform services spanning orchestration, APIs, workflow automation, integrations, and content systems.
Enable downstream products and services such as AvaTax, ATC, and ATR to interact with platform capabilities through modern integration interfaces, including MCP where appropriate.
Define measurable engineering and operational metrics tied to platform reliability, quality, productivity, adoption, and business impact.
Partner closely with Product, Content Research, Applied AI, Architecture, and business stakeholders to align platform investments with company priorities.
Build and develop a high-performing engineering organization with strong technical depth, accountability, and execution discipline.
Drive pragmatic adoption of AI across engineering workflows, planning, delivery operations, observability, and decision-making processes.
Ensure governance, security, and responsible AI practices are incorporated into platform design and operational processes.