Note: The job is a remote job and is open to candidates in USA. Insight Global is 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.
Responsibilities
- 8+ 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 .NET, C# and backend APIs, building secure, scalable enterprise integrations
- Deep experience with Azure services, including Service Bus, Event Hub, Blob Storage, Key Vault, and Azure AI Services
- Hands‑on experience integrating LLMs and AI APIs (e.g., Cohere, OpenAI/ChatGPT, Claude)
- 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
- 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 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.)
- Python, especially for MCP connectors and AI integrations
- Experience with Snowflake, enterprise data platforms, or Amazon Bedrock
- Knowledge of microservices architectures
- Familiarity with CI/CD pipelines and DevOps practices
- Exposure to agentic AI patterns, autonomous workflows, or AI automation frameworks
Skills
- 8+ 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 .NET, C# and backend APIs, building secure, scalable enterprise integrations
- Deep experience with Azure services, including Service Bus, Event Hub, Blob Storage, Key Vault, and Azure AI Services
- Hands‑on experience integrating LLMs and AI APIs (e.g., Cohere, OpenAI/ChatGPT, Claude)
- 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
- 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 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.)
- Python, especially for MCP connectors and AI integrations
- Experience with Snowflake, enterprise data platforms, or Amazon Bedrock
- Knowledge of microservices architectures
- Familiarity with CI/CD pipelines and DevOps practices
- Exposure to agentic AI patterns, autonomous workflows, or AI automation frameworks
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