Technical Lead Engineer; MCP​/AI

Job Description

We are seeking a Technical Lead Engineer to lead enterprise AI connectivity, governance, and architecture initiatives within a regulated financial services environment. This role is responsible for designing, governing, and enabling Model Context Protocol (MCP)–based integrations that connect AI platforms, internal enterprise tools, and data systems in a secure, observable, and compliant manner. The Lead Engineer will help lead enterprise AI enablement initiatives in a regulated financial services environment, focused on Model Context Protocol (MCP) architecture, secure connectivity, and AI governance.

This role owns solution architecture design, .NET- and Azure-based integrations, and prompt engineering observability, enabling safe reuse of existing AI capabilities across internal tools and platforms. The work heavily involves email connectivity and enablement using MCP, limited agentic AI, and deep experience integrating LLMs and APIs (e.g., ChatGPT/OpenAI, Claude, Cohere) via Azure services while driving designs through governance and architecture review councils.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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10+ years of experience as an Engineer with Lead experience

• Financial services/banking experience in regulated enterprise environments
• Strong backend API and .NET experience building enterprise integrations and APIs
• Strong Azure services experience, including Service Bus, Event Hub, Blob Storage, and Key Vault (Azure AI Services required)
• Hands‑on experience with LLMs and AI APIs (e.g., OpenAI/ChatGPT, Claude, Cohere)
• Deep experience with Model Context Protocol (MCP): MCP architecture, servers, connectors, and custom MCP integrations
• Experience producing solution architecture diagrams and owning designs through governance and review councils
• Experience with prompt engineering monitoring and observability, access management, and secure enterprise connectivity (AD groups, firewalls)
• Experience connecting MCP to internal tools/platforms (e.g., Confluence, AI aggregation platforms such as Snowflake others) – Python (especially for MCP connectors and AI integrations)
• Experience integrating with Snowflake or enterprise data warehouses – specifically Snowflake and Amazon Bedrock
• Experience with agentic AI