AI Automation Lead II

Overview

The Commercial Scaled Intelligence (CSI) team is an AI-first team dedicated to delivering actionable commercial insights and scalable automation to drive revenue growth and operational efficiency across the company. The team focuses on intelligence generation, predictive analytics, and workflow automation to enable data-driven decision-making and optimize commercial performance.

We are looking for an AI Automation Lead to design, architect, and scale intelligent automation solutions that transform how our Commercial organization operates. You'll lead the technical strategy for AI-driven workflows, mentor team members, and partner with Commercial leadership (Sales, Partnerships, Operations) to identify high-impact automation opportunities that drive measurable revenue outcomes.

This role is ideal for someone with 5–8 years of experience in data engineering, automation, or platform engineering who wants to lead AI initiatives at the intersection of technology, integrations, and business enablement.

About the Job

• Lead technical strategy and architecture for AI automation across the Commercial organization, identifying high-ROI opportunities and translating business requirements into scalable solutions.
• Design and build production-grade AI tools that understand natural language, provide actionable insights, generate reports, and automate complex workflows such as campaign planning, ticket management, and sales enablement.
• Architect reliable, scalable integrations across internal systems and third-party SaaS (REST/GraphQL APIs, webhooks, OAuth, JWT), establishing best practices for rate limiting, retries, idempotency, and error handling.
• Lead development of multi-step AI agent architectures using frameworks like LangChain, LangGraph, or MCP, with appropriate human-in-the-loop controls and production-ready evaluation.
• Establish and enforce AI safety and reliability standards including guardrails, evaluation frameworks, fallback logic, RBAC, audit trails, and PII protections across all AI systems.
• Design and optimize data pipelines (SQL, Python, dbt) that power AI agents at scale, ensuring reliability, observability, and performance.
• Create frameworks and templates for rapid prototyping and deployment of new automations, enabling faster time-to-value for future projects.
• Drive adoption by building intuitive UIs and self-serve experiences (e.g., Slack apps, low-code internal tools) and creating documentation that makes AI tools accessible to non-technical users.
• Partner with Sales, Partnerships, Product, Engineering, and Data Science leadership to prioritize initiatives, align on roadmaps, and ensure solutions drive measurable business outcomes.
• Mentor and guide other engineers on AI/LLM best practices, prompt engineering, evaluation frameworks, and production deployment patterns.
• Champion DevOps excellence including CI/CD, automated testing, observability, alerting, and incident response.
• Enforce security and compliance best practices across all automations and data workflows.
• Measure and communicate impact through clear metrics tied to business outcomes (time saved, revenue enabled, efficiency gains).

About You

Minimum Qualifications

• 5–8 years experience in AI, automation, data engineering, or analytics engineering.
• Proven track record of designing and deploying AI/automation solutions that drove measurable business impact.
• Deep proficiency in SQL and Python; extensive experience building and operating production ETL/ELT pipelines.
• Strong experience designing and consuming APIs/webhooks and building reliable services (FastAPI, Flask, or Node.js) at scale.
• Production experience with dbt and modern cloud data warehouses (Snowflake, BigQuery, Databricks).
• Hands-on experience incorporating AI/LLMs into production workflows, including prompt engineering, retrieval strategies, evaluation, and deployment.
• Expert knowledge of Git, CI/CD, automated testing, and event-driven systems (queues, pub/sub, webhooks).
• Experience leading technical initiatives and mentoring other engineers.
• Excellent communication skills: able to translate complex technical concepts for business stakeholders and influence cross-functional teams.
• Experience with at least one data visualization tool (Tableau, Mode, Power BI, Looker, or similar).
• Hands-on experience with workflow automation and low-code development platforms (Zapier, n8n, Gumloop, Superblocks).

Preferred Qualifications

• Led development of AI agent systems or automation platforms adopted by multiple business teams.
• Deep experience with AI orchestration frameworks like A2A, LangChain, LangGraph, or Model Context Protocol (MCP).
• Production experience with vector databases, RAG architectures, and AI evaluation frameworks (e.g., Ragas, DeepEval, LangSmith).
• Built and maintained Slack apps or other lightweight internal tools with high adoption rates.
• Expert-level API design skills including OpenAPI, contract testing, rate limiting, and monitoring.
• Production cloud experience (AWS, GCP, or Azure) including containerization (Docker/K8s) and infrastructure-as-code (Terraform, CloudFormation).
• Deep integration experience with business tools (Salesforce, Slack, Google Workspace, Jira/Linear).
• Experience establishing best practices and technical standards for a team or organization.
• Prior exposure to e-commerce, retail analytics, or ad tech is a plus.