Senior AI Software Engineer (Healthcare)

The Phia Group is a service- oriented organization assisting employee health plans nationwide. We provide our clients with innovative cost-cutting solutions and constantly expanding service offerings. We continue to enjoy growth thanks to our most valuable resource – our talented and committed team.

At The Phia Group, whose mission is to provide high quality yet affordable healthcare to American employees and their families, you can look forward to not only unparalleled benefits for yourself but also being immersed in a company that was named one of USA Today’s Top Workplaces for 2025. Meanwhile, from a regional perspective, both The Boston Globe and Louisville Business First also recognized our unwavering commitment to upholding an internal culture of inclusivity, enjoyment, and empathy for our valued employees by listing The Phia Group in their respective lists for the Top Places to Work in 2025.

About the Role

We are seeking a forward-thinking AI Software Engineer to design, build, and scale intelligent applications powered by modern AI technologies. This role goes beyond traditional software engineering — focusing on Generative AI, Retrieval-Augmented Generation (RAG), and AI-assisted development using tools like Claude, GPT, and other LLM platforms.

You will play a key role in shaping our AI roadmap by building production-grade AI systems, optimizing developer productivity with AI tools, and integrating intelligent workflows into our healthcare platforms.

Key Responsibilities

AI Engineering & GenAI Development

• Design and implement RAG (Retrieval-Augmented Generation) pipelines using modern vector databases and embeddings.
• Build and optimize LLM-powered applications (chatbots, copilots, automation agents).
• Leverage tools like Claude, GPT, and AI coding assistants to accelerate development and improve code quality.
• Develop agentic AI workflows using frameworks that enable reasoning, tool usage, and multi-step decision-making.
• Design and orchestrate multi-agent workflows including orchestrator/supervisor patterns, agent handoffs, and tool routing

Azure AI & Cloud Integration

• Architect and deploy AI solutions using Azure AI Foundry / Azure OpenAI / Azure ML.
• Manage scalable deployments using Azure Kubernetes Service (AKS), Docker, and Helm.
• Implement semantic search and vector indexing using tools like Qdrant or Azure Cognitive Search.
• Build model-agnostic AI routing layers ( this is to abstract the LLM provider dependencies and create pipelines where we can change models on the fly)

Full-Stack + AI Integration

• Build and maintain full-stack applications integrating AI services:
  • Frontend: Angular / modern JS frameworks
  • Backend: FastAPI, Spring Boot, Node.js
  • Data: SQL/NoSQL systems
• Integrate AI services into existing enterprise systems and APIs.

AI-Driven Development & Productivity

• Use AI tools (Claude, Copilot, etc.) for:
  • Code generation and refactoring
  • Debugging and optimization
  • Test generation and documentation
• Continuously evaluate and adopt new AI tools to improve engineering velocity.

DevOps & Scalability

• Build and maintain CI/CD pipelines (Azure DevOps) for AI applications.
• Optimize system performance, scalability, and reliability of AI workloads.
• Monitor and improve model performance, latency, and cost efficiency.

Required Qualifications

• Bachelor’s degree in Computer Science, IT, or related field + relevant experience.
• Strong experience with:
  • Python (FastAPI preferred)
  • Modern backend or full-stack frameworks
• Hands-on experience with:
  • RAG architecture, embeddings, and vector databases
  • LLMs (GPT, Claude, or similar)
• Experience deploying applications on Azure (AKS, Azure AI services).
• Familiarity with Docker, Kubernetes, and cloud-native architectures.
• Experience with MS SQL, Azure storage, Azure App services, APIM.

Preferred Qualifications

• Experience with Azure AI Foundry or similar GenAI platforms.
• Strong understanding of:
  • Prompt engineering
  • Context management in LLMs
  • Fine-tuning / evaluation techniques
• Experience with vector DBs like Qdrant, Pinecone, or Azure Cognitive Search.
• Exposure to agent frameworks (LangChain, Semantic Kernel, AutoGen, etc.).
• Prior experience building AI copilots or internal AI tools.

Working Conditions / Physical Demands
Sitting at workstation for prolong periods of time. Extensive computer work. Workstation …