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
1. 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.
2. 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.
3. 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).
4. 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.
