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Wunderman Thompson

AI Enterprise Senior Technical Lead

Katowice, Poland; Poznań, Poland; VML Enterprise Solutions PolandPoland
Staff · Freelance
POSTED 30 OCTVERIFIED 4H AGO
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Pay · H-1B filings
$99k
median · n=4 · FY26
Open for
4d
since 30 Oct
H-1B · FY26
8
3 PERM
Hiring · 30d
381
+1 net · open roles
AzureLLMs

Who We Are

VML is a global creative company that combines brand experience, customer experience, and commerce to create connected brands that drive growth. Guided by a Human First philosophy, VML is known for its innovative work for brands and consistently ranks among the world’s leading creative companies, including the WARC Creative 100. VML’s global network spans 55+ markets with principal offices in Buenos Aires, Kansas City, London, New York, São Paulo, Shanghai and Singapore.

VML is part of WPP, the trusted growth partner for the world's leading brands. Powered by exceptional talent and our agentic marketing platform WPP Open, WPP unites cutting-edge media intelligence and data solutions, creativity, production, enterprise solutions and expert strategic counsel.

For more information, please visit www.vml.com and follow along on LinkedIn #WeAreVML.

The opportunity

We are looking for an AI Enterprise Technical Lead to join a high-profile enterprise AI project for a major global brand.

This is a high-impact technical leadership role combining ownership of enterprise AI delivery, client-facing discovery and technical workshops with strong architectural influence and a balance between technical leadership and hands-on engineering.

You will help shape and deliver a secure, enterprise-grade AI platform built around Microsoft Azure, LLMs, agentic workflows, enterprise knowledge and integrations.

A key part of the role is understanding AI as part of a larger enterprise architecture. You will make pragmatic decisions about where LLMs and agents add value, where deterministic software is the better choice, how enterprise knowledge should be retrieved and how AI capabilities should integrate with existing platforms.

What you’ll get to do

  • Lead technical discovery and solution design, translating business workflows into scalable AI solutions.
  • Shape architecture across AI agents, orchestration, RAG/retrieval, Azure services and enterprise integrations.
  • Define clear boundaries between AI/LLM capabilities and deterministic application logic.
  • Design agent workflows, context management, tool usage and appropriate human-in-the-loop controls.
  • Shape RAG and enterprise knowledge solutions, including retrieval and use of trusted sources.
  • Design integrations between AI workflows, APIs and existing enterprise platforms.
  • Ensure appropriate approaches to security, identity and access, governance, observability and auditability.
  • Turn discovery outcomes into architecture, technical scope and an actionable implementation backlog.
  • Lead engineers throughout delivery, providing hands-on guidance, code reviews and support with complex technical decisions.
  • Establish effective approaches to AI evaluation, testing and continuous improvement.

What you should have

  • Strong commercial experience designing and delivering AI/GenAI solutions in enterprise environments.
  • Strong understanding of LLMs, agentic architectures, RAG and workflow orchestration.
  • Hands-on experience building AI solutions and integrating them with application services and APIs.
  • Good practical knowledge of Microsoft Azure and Azure AI services.
  • Strong understanding of software architecture, API design and enterprise integration patterns.
  • Experience combining LLM-based capabilities with deterministic application logic.
  • Practical understanding of context engineering, retrieval, structured model outputs and AI evaluation.
  • Understanding of security, identity and access, governance and human oversight in enterprise AI solutions.
  • Proven experience leading technical discovery and solution design.
  • Experience providing technical leadership while remaining hands-on when needed.
  • Strong client-facing communication skills and the ability to explain complex technical decisions and trade-offs.
  • Fluency in English.

Bonus points if you have

  • Experience designing multi-agent or agentic workflow architectures.
  • Experience building enterprise RAG and knowledge retrieval solutions.
  • Experience with LLMOps/MLOps and systematic AI evaluation.
  • Experience implementing AI guardrails or model routing.
Source · Wunderman Thompson · GreenhouseFirst seen 2 Nov1 editsOriginal ↗Method