AI Engineer

Job Description

We are seeking a Senior AI Engineer to design, build, and enable secure, scalable enterprise AI solutions within a regulated financial services environment. This role focuses on implementing Model Context Protocol (MCP)–based integrations that connect LLM platforms, internal enterprise tools, and data systems in a compliant, observable, and production‑ready manner.

The AI Engineer will be highly hands‑on, developing .NET- and Azure‑based AI integrations, building and integrating GenAI / RAG pipelines, custom models, and limited agentic AI workflows. This role partners closely with architecture, security, and governance teams to ensure AI solutions meet enterprise standards while enabling reuse and scale across the organization.

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. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

• 7+ years of experience in software engineering, with deep hands‑on focus in .Net, Azure services, and backend engineering

• Experience working in financial services or other regulated enterprise environments

• Strong experience with backend APIs, building secure, scalable enterprise architecture documents, requirements, epics, integrations

• Deep experience with Azure

• Experience building out MCP servers from scratch and deploying into production

• Hands‑on experience integrating LLMs (e.g., Cohere, OpenAI/ChatGPT, Claude) and agents, and agentic AI delivery

• Proven expertise with Model Context Protocol (MCP), including MCP architecture, servers, connectors, and custom integrations

• Strong experience designing and implementing secure enterprise AI connectivity, including access controls, observability, and governance from a security perspective

• Experience with prompt engineering, model fine‑tuning, monitoring, and AI observability

Familiarity with enterprise security concepts (AD groups, firewalls, secure connectivity)

• Experience integrating AI/MCP with internal enterprise tools and mutiple systems, sources, and platforms (e.g., Confluence, data platforms such as Snowflake)

• Ability to contribute to solution architecture artifacts and participate in architecture and governance reviews

• Strong communication skills, able to engage effectively with technical, delivery, and business stakeholders

• Experience working in Agile environments (Scrum, Kanban, etc.)

• thrive in a fast moving environment and solution oriented

• Python experience

• Exposure to agentic AI patterns, autonomous workflows, or AI automation frameworks - Experience with Snowflake

• Experience with Amazon Bedrock

• master's degree