AI Engineer

We are seeking a hands-on AI Engineer to support the ongoing operation, modernization, and enhancement of AI-enabled applications for the Client. This role will involve working with confidential and regulated financial and examination data, so the ideal candidate must have strong technical skills, secure development experience, and excellent communication abilities.

The AI Engineer will primarily work with Python, modern web frameworks such as FastAPI, and cloud services within Microsoft Azure. The candidate will be responsible for developing, maintaining, deploying, and supporting AI-powered applications and backend services. This position requires practical experience building applications powered by large language models such as OpenAI GPT, Anthropic Claude, or Google Gemini.

This is an applied technical role in an AI-assisted software development environment. The successful candidate should be comfortable using modern AI coding assistants for writing, reviewing, debugging, and improving code while also validating the output and ensuring production-quality delivery.

The candidate will work closely with business users, analysts, technical teams, and the Connecticut AI Lab, which provides architectural guidance, shared infrastructure, and engineering support for AI-enabled tools across agencies.

Key Responsibilities

Maintain, enhance, and extend existing AI-enabled applications and supporting services.

Develop application logic, backend services, and web APIs using Python and modern web frameworks such as FastAPI.

Build, test, and support applications powered by large language models, including OpenAI GPT, Anthropic Claude, Google Gemini, or similar platforms.

Compare and evaluate AI models based on task performance, accuracy, cost, latency, and reliability.

Configure, deploy, monitor, and maintain applications and services in cloud environments.

Deploy and support services using Microsoft Azure technologies such as Azure App Service, Azure Storage, Azure Key Vault, and related services.

Participate in requirements gathering, design discussions, and project planning sessions with business and technical stakeholders.

Prepare source code, debug issues, correct errors, and maintain software quality.

Use Git-based source control, branching, pull requests, and code review workflows.

Document technical procedures, system workflows, application processes, and deployment steps.

Apply secure development practices when working with confidential, regulated, or sensitive data.

Collaborate with client teams and the clients AI Lab to support AI application development and modernization efforts.

Participate in the evaluation of new AI tools, frameworks, models, and related technologies.

Minimum 3 years of Python development experience in a web application environment, including application logic and web APIs.

Minimum 2 years of experience building applications powered by large language models such as OpenAI GPT, Anthropic Claude, Google Gemini, or similar LLM platforms.

Minimum 2 years of professional experience comparing and selecting AI models, including A/B testing or evaluating model performance for specific tasks.

Strong understanding of modern software development practices, systems analysis, design, debugging, and application support.

Experience working with modern web frameworks such as FastAPI, Flask, or Django.

Experience using AI-assisted software development tools to write, review, debug, and improve code.

Strong understanding of secure development practices and proper handling of confidential or regulated data.

Excellent oral and written communication skills are required.

Ability to take a user request from intake through design, development, testing, deployment, and production support with appropriate guidance.

Preferred Skills

Experience deploying applications and supporting services in cloud environments.

Experience with Microsoft Azure services, including Azure App Service, Azure Storage, Azure Key Vault, Azure Functions, or related services.

Experience using Git, GitHub, Azure DevOps, pull requests, and code review workflows.

Previous experience working directly with a state government agency on AI development projects.

Experience with prompt engineering, RAG, embeddings, vector databases, model evaluation, or AI application monitoring.

Experience working with financial, regulatory, banking, government, or other sensitive data environments., The ideal candidate is a hands-on AI application engineer with strong Python backend development experience, practical LLM application development skills, Azure deployment experience, and the ability to work in a secure government environment. This person should be able to communicate clearly with both technical and non-technical stakeholders and deliver reliable, production-ready AI-enabled applications.