Gen AI Engineer

Publicis Client Level & Job Title: Senior Manager GenAI Engineer
Req # to submit to: 2026-172148
Client: Wellington (Keep Confidential and disclose to candidates as a leading Financial Services firm)
Openings: 1
Rate: $200/hr
Project overview:
Looking for AI Engineering leader with extensive experience delivering AI solutions into the enterprise. This would include standing up foundational agentic capabilities that will be leveraged across the organization. This is a great opportunity for someone who wants to lead the building of core AI capabilities in a greenfield environment. Proven track record of partnering with top asset managers is preferred, but strategic AI delivery experience is critical. Opportunity to design and implement scalable AI solutions that enhance investment decision-making, operational efficiency, risk management, and client experience.
Top 3 Skills Required:

• Agentic AI solution architecture experience – need genuine experience building and deploying agents in the enterprise.
• Solution-oriented mindset – this is not a heads down engineering role. The ability to design and present on the solution architecture is required.
• Client-oriented thinking – Need to have a genuine interest in partnering with the client to deliver on their goals and objectives

Industry Experience: Financial Services – Asset Management strongly preferred
Expected Start Date: ASAP
End Date: 12/31/26 (strong likelyhood of extension)
Location: Boston- Client site 4 days per week
Interview Process (including any client interviews): 3 rounds- two internal interviews and a client interview
Requirements Provided:
We are seeking a highly skilled Generative AI Engineer to design, build, and deploy intelligent AI agents that solve complex business challenges. The ideal candidate will have hands-on experience with modern AI development lifecycle tools, agentic frameworks, and enterprise AI platforms, with the ability to take solutions from concept through production deployment.
Key Responsibilities

• Design, develop, and deploy AI agents and agentic workflows using modern Generative AI frameworks
• Build scalable solutions leveraging Large Language Models (LLMs), retrieval-augmented generation (RAG), orchestration frameworks, and autonomous agents.
• Develop and optimize multi-step AI workflows that integrate with enterprise systems, APIs, and business processes.
• Collaborate with product, engineering, and business stakeholders to identify AI use cases and deliver production-ready solutions.
• Evaluate emerging AI technologies, frameworks, and tools to improve development efficiency and solution effectiveness.
• Ensure AI solutions meet enterprise standards for scalability, security, performance, and maintainability.

Required Qualifications

• Experience with Microsoft Fabric and in building and deploying AI agents on Azure AI Foundry.
• Strong hands-on experience with at least one AI-assisted development platform:
  • Claude Code
  • GitHub Copilot
  • Cursor
  • Windsurf
  • Slingshot
• Experience building, testing, and deploying agentic AI solutions in enterprise environments.
• Solid understanding of Large Language Models (LLMs), prompt engineering, AI workflow orchestration, tool calling, memory management, and agent architectures.
• Strong software engineering fundamentals with experience in API integration, system design, and application development.

Preferred Qualifications

• Proven experience designing and implementing AI agents using modern Generative AI frameworks such as:
  • LangGraph
  • LangChain
  • LangSmith
  • Similar agent orchestration and observability frameworks
• Familiarity with cloud-native AI architectures and MLOps best practices.
• Experience integrating AI solutions with enterprise data platforms and business applications.

Ideal Candidate
The successful candidate combines deep Generative AI expertise with strong software engineering skills and a passion for building intelligent, production-grade AI solutions. They stay current with the rapidly evolving AI ecosystem and have practical experience turning AI concepts into measurable business outcomes.