Senior Software Engineer (GenAI)

[Confidential Healthcare Client]

Sr. Software Engineer – Generative AI

Location: REMOTE
Contract Term: 6 months+ with likely extensions
Employment Type: W2 (H1B sponsorship and C2C eligible)
Pay Rate: $55–$70/hr
Client Industry: Healthcare / Hospital Innovation

Role Overview:

A leading hospital system is seeking a Sr. Software Engineer – Gen AI to join its growing team. This role is ideal for a self-driven engineer who thrives in ambiguity and enjoys building end-to-end generative AI applications from the ground up. You’ll be developing solutions across AWS and Azure, with a strong emphasis on compliance, scalability, and production-level readiness in healthcare environments.

Key Responsibilities:

• Design and implement generative AI applications using LLMs (e.g., GPT, Claude, LLama), foundation models, and agentic frameworks (LangChain, Amazon Bedrock Agents, Azure Semantic Kernel, AutoGen).
• Develop and deploy AI systems using:
  • AWS: Bedrock, SageMaker, Kendra, Lambda, HealthLake
  • Azure: OpenAI, Azure ML, Cognitive Search, Functions, Health Data Services
• Evaluate and integrate third-party platforms such as OpenAI, Anthropic, and Cohere.
• Implement LLM evaluation frameworks (RAGAS, hallucination checks, human-in-the-loop).
• Solve technical challenges related to scale, performance, and regulatory compliance.
• Build internal tools and UIs using React, REST, and GraphQL to operationalize AI systems.

Required Experience:

• 3+ years of hands-on AI/ML development experience, with 1+ year in generative AI (LLMs, RAG pipelines, agents).
• Proven ability to work independently and drive projects to completion in a fast-paced environment.
• Expertise in Python, with experience in TypeScript or JavaScript.
• Production experience with:
  • LLM frameworks such as LangChain and LlamaIndex
  • Vector databases (OpenSearch, Pinecone, FAISS, Weaviate)
• Strong CI/CD pipeline experience using modern DevOps practices and Git workflows.
• Familiarity with regulated environments (e.g., HIPAA) is a strong plus.
• Exposure to traditional ML (e.g., pandas, scikit-learn, EDA).
• Full-stack development proficiency (React, REST/GraphQL).
• Experience with observability tools like CloudWatch and Grafana.

Preferred Certifications:

• AWS Certified Developer or Solutions Architect
• Microsoft Certified: Azure AI Engineer

Education:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field