The Role
Build and deploy production-grade agentic AI workflows across Finance, HR, and AdOps. Responsibilities include LLM engineering, API integrations, process discovery, automation prioritization, prototyping, observability, governance, user training, change management, and specialized advertising-operations automation. The role requires taking AI solutions from concept through deployment and adoption while ensuring reliability, maintainability, and GDPR-aligned data protection.
Summary Generated by Built In
About the Role
What You’ll Do1. Architecture, Build & Deployment
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.
- 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 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.
- 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).
- 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.
- 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.
Information Security & ISO 27001 Compliance
Security is at the heart of everything we do. In this role, you will be strictly required to uphold our Information Security Management System (ISMS) policies in alignment with ISO/IEC 27001 standards. Responsibilities include safeguarding sensitive asset data, completing mandatory security awareness training, reporting potential security incidents or vulnerabilities immediately, and ensuring that daily operations comply with our rigorous data protection protocols.
Skills Required
- 4–7 years of experience in technical automation, AI engineering, or business transformation delivery
- Proven experience building and deploying LLM-powered tools or agents in production
- Proficiency in Python or JavaScript
- Mastery of at least one automation platform: n8n, Make, or LangChain
- Experience integrating business systems using APIs and webhooks
- Strong stakeholder management skills
- Ability to independently move projects from specification through live deployment
- Compliance with ISO/IEC 27001 information security policies and data protection protocols
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The Company
What We Do
DataBeat helps enterprises and publishers navigate data analytics and ad technology through advanced analytics, programmatic advertising, and ad-operations support. Its capabilities include big-data engineering, data visualization, and yield optimization, helping clients turn data into actionable, ROI-boosting insights and improve advertising performance. The Princeton-based company provides media, advertising, and analytics solutions across complex, data-driven digital ecosystems for business customers and enterprise teams worldwide.
