AI Engineer

Insight Global

Los Angeles, CA, United States

16 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

8 years minimum

Working hours

Regular working hours

Job source

www.juju.com

Tech stack

.NET Framework Application Programming Interfaces (APIs) Agile Methodology Artificial Intelligence Confluence Microsoft Azure C Sharp (Programming Language) Data Systems DevOps Python (Programming Language) Scrum Methodology Azure Machine Learning

+15 more

Software Engineering Systems Integration Enterprise Data Management Large Language Models Snowflake Prompt Engineering Firewalls (Computer Science) Enterprise Integration Data Management Virtual Agents Network Server GPT Key Vault Web Api Microservices

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.

Requirements

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