Senior Manager GenAI Engineer

enableIT; Boston (MA); On-site; USD 180,000 - 260,000; Full time

Job summary

enableIT is seeking a Senior Manager GenAI Engineer to lead the design, development, and deployment of enterprise-grade Generative AI solutions for a leading financial services client. The role is onsite four days per week at the client site in Boston, with ASAP start and a long contract with extension potential.

The ideal candidate combines hands-on engineering with solution architecture, stakeholder engagement, and client-facing leadership to translate business needs into scalable AI

Qualifications

• Proven experience building, testing, and deploying agentic AI solutions in enterprise environments.
• Hands-on experience with Azure AI Foundry.
• Experience with Microsoft Fabric and enterprise data ecosystems.
• Strong software engineering background (Python, API development, system design).
• Experience with AI-assisted development platforms (Cursor, Windsurf, Slingshot).

Responsibilities

• Design, build, and deploy AI agents and agentic workflows for enterprise use cases.
• Define scalable GenAI and agentic AI solution architectures across applications, data, models, tools, and orchestration layers.
• Build multi-step AI workflows leveraging LLMs, RAG, tool calling, memory, orchestration, and autonomous agent patterns.
• Develop and deploy AI agents using Azure AI Foundry and integrate them with enterprise platforms and systems.
• Leverage Microsoft Fabric and enterprise data platforms to support AI-powered solutions and workflows.
• Integrate AI agents with enterprise APIs, applications, databases, and business processes.
• Evaluate and adopt modern AI frameworks, platforms, development tools, and agent technologies.
• Establish reusable patterns, frameworks, and foundational capabilities for enterprise agentic AI adoption.
• Ensure solutions meet enterprise requirements for security, scalability, reliability, performance, observability, and maintainability.
• Partner with product, engineering, data, architecture, and business stakeholders to translate business objectives into technical solutions.
• Lead technical discussions and present solution architecture, design decisions, tradeoffs, and implementation approaches to senior stakeholders.
• Support the full AI engineering lifecycle from ideation and prototyping through testing, deployment, monitoring, and production support.
• Stay current with rapidly evolving Generative AI, agentic AI, and cloud-native AI technologies.

Skills

Agentic AI design

Python

API development

System design

RAG

Multi-agent workflows

Memory management

Communication skills

Client engagement

Tools

Azure AI Foundry

Microsoft Fabric

Cursor

Windsurf

Slingshot

Job description

Work Model: Onsite – 4 days per week at client site

Contract: Long Contract (strong possibility of extension)

Start Date: ASAP

Interview Process: 3 rounds – 2 internal interviews + 1 client interview

Position Overview:

We are seeking a Senior Manager GenAI Engineer to lead the design, development, and deployment of enterprise-grade Generative AI and agentic AI solutions for a leading financial services organization.

This is a high-impact opportunity for an AI engineering leader who enjoys working in a greenfield environment and wants to establish foundational agentic AI capabilities that can be leveraged across the enterprise.

The ideal candidate combines strong hands‑on engineering expertise with solution architecture, stakeholder engagement, and client‑facing leadership. You will work closely with business and technology stakeholders to identify high‑value AI use cases, design scalable solutions, and take AI capabilities from concept through production.

Experience partnering with asset management or investment management organizations is highly preferred.

Key Responsibilities:

• Design, build, and deploy AI agents and agentic workflows for enterprise use cases.
• Define scalable GenAI and agentic AI solution architectures across applications, data, models, tools, and orchestration layers.
• Build multi‑step AI workflows leveraging LLMs, RAG, tool calling, memory, orchestration, and autonomous agent patterns.
• Develop and deploy AI agents using Azure AI Foundry and integrate them with enterprise platforms and systems.
• Leverage Microsoft Fabric and enterprise data platforms to support AI‑powered solutions and workflows.
• Integrate AI agents with enterprise APIs, applications, databases, and business processes.
• Evaluate and adopt modern AI frameworks, platforms, development tools, and agent technologies.
• Establish reusable patterns, frameworks, and foundational capabilities for enterprise agentic AI adoption.
• Ensure solutions meet enterprise requirements for security, scalability, reliability, performance, observability, and maintainability.
• Partner with product, engineering, data, architecture, and business stakeholders to translate business objectives into technical solutions.
• Lead technical discussions and present solution architecture, design decisions, tradeoffs, and implementation approaches to senior stakeholders.
• Support the full AI engineering lifecycle from ideation and prototyping through testing, deployment, monitoring, and production support.
• Stay current with rapidly evolving Generative AI, agentic AI, and cloud‑native AI technologies.

Required Qualifications:

• Proven experience building, testing, and deploying agentic AI solutions in enterprise environments.
• Strong hands‑on experience building AI agents using Azure AI Foundry.
• Experience with Microsoft Fabric and enterprise data ecosystems.
• Strong understanding of:
• Tool/function calling
• AI workflow orchestration
• Memory management
• Retrieval‑Augmented Generation (RAG)
• Multi‑step and multi‑agent workflows
• Strong software engineering background with experience in:
• Python and/or other modern programming languages
• API development and integration
• System design and architecture
• Experience with at least one AI‑assisted development platform such as:
• Cursor
• Windsurf
• Slingshot
• Strong communication and presentation skills with the ability to explain complex AI architectures to technical and business audiences.
• Demonstrated ability to work directly with clients and senior stakeholders to define solutions and drive delivery.