About The Role

This is a high-impact, hybrid role designed for a technical operator. You aren't just strategizing about AI; you are building it and ensuring it sticks. Reporting directly to the Head of Agentic Transformation, you will bridge the gap between business strategy and production-ready automation.

As the Lead Agentic AI Solutions Manager, you will own the entire lifecycle of transformation: from mapping messy human processes and scoping automation briefs to writing the code, connecting the APIs, and training teams to adopt their new AI colleagues. If you are a builder who loves seeing your work run in production and a strategist who cares about the human impact of technology, this role is for you.

What You'll Do

Architecture, Build & Deployment
Design & Ship Agents: Build production-ready agentic workflows using tools like LangChain, LangGraph, n8n, or Make across Finance, HR, and AdOps.
LLM Engineering: Develop natural language query interfaces, intelligent routing agents, and RAG-powered document processing pipelines.
Technical Integration: Own the API layer (REST, webhooks, JSON, OAuth) between business systems like CRMs, HR platforms, and Ad Servers.
Prototyping: Rapidly move from a whiteboard concept to a minimum viable agent, testing with real users and iterating based on performance.
Process Discovery & Scoping
Process Mapping: Audit current workflows to identify bottlenecks, manual data entry points, and high-value automation opportunities.
Strategic Prioritization: Maintain and sequence a backlog of transformation initiatives based on ROI, time-savings, and technical feasibility.
Briefing: Translate complex business pain points into clear technical specifications with defined edge cases and success criteria.
Change Management & Adoption
Make it Stick: Own the human side of deployment—conducting training sessions, writing user guides, and providing hands-on support during transitions.
Relationship Building: Work closely with team leads to handle resistance and ensure that automated tools are actually utilized by the workforce.
Governance & Reliability: Set up observability (logging, alerting) and write runbooks so that automations are maintainable and compliant (GDPR/Data Privacy).
Specialized AdOps Automation
Campaign Lifecycle: Automate pacing alerts, budget tracking, and delivery discrepancy resolution to reduce manual overhead in media operations.
Reporting Sync: Build automated data pipelines between DSPs/SSPs and internal reporting tools to eliminate manual data reconciliation.

What You'll Need

Must-Have Experience

4–7 years in technical automation, AI engineering, or business transformation delivery.
Hands-on AI Delivery: Proven experience building and deploying LLM-powered tools or agents in a production environment (not just toy projects).
Technical Stack: Proficiency in Python or JavaScript for custom scripting and mastery of at least one automation platform (n8n, Make, LangChain).
The Integration Mindset: Comfortable connecting systems that aren't designed to talk to each other using APIs and webhooks.
Operational Excellence: Strong stakeholder management skills and the ability to move a project forward independently from spec to live status.

Agentic AI Transformations