Senior Software Engineer - AWS, Python & React

Job Responsibilities

• Full Stack Development (Backend)
• Develop high-performance applications for AI-assisted workflows and decision systems
• Cloud (AWS)
• Architect and deploy applications on AWS (Lambda, ECS/EKS, API Gateway, S3, DynamoDB, Aurora, Bedrock/SageMaker)
• Design event-driven and microservices architectures for scalable AI workloads
• Implement Infrastructure-as-Code (Terraform/CloudFormation)
• CI/CD & Engineering Excellence
• Build and optimize CI/CD pipelines (GitHub Actions/Azure DevOps/Jenkins) for automated builds, testing, and deployments
• Apply MLOps practices including model lifecycle, versioning, and monitoring
• Improve performance, reliability, observability, and cost efficiency of AI inference systems

Key Skills (Must-Have)

• Backend: Python (FastAPI/Flask), API design
• Cloud: AWS (Lambda, ECS/EKS, API Gateway, S3, DynamoDB)
• DevOps: CI/CD, Docker, Kubernetes, Terraform
• Data: SQL/NoSQL, vector databases

Required Qualifications

• 8+ years of full stack engineering experience, with strong backend and frontend expertise
• Strong programming skills in Python and experience with RESTful API development
• Proven experience working on AWS cloud platform (compute, storage, networking, IAM, monitoring)
• Strong understanding of CI/CD pipelines, DevOps practices, and containerization (Docker/Kubernetes)
• Experience integrating AI/ML models into production applications

Preferred Qualifications

• Hands-on experience with React.js (hooks, state management, component design)
• Experience with Agentic AI / Generative AI systems (LLMs, RAG, orchestration frameworks)
• Familiarity with vector databases (Pinecone, FAISS, OpenSearch) and semantic search
• Exposure to MLOps ecosystems (model registry, pipelines, evaluation frameworks)
• Experience in microservices architecture and event-driven systems
• Prior experience in healthcare/claims domain or regulated environments (preferred)

Healthcare domain exposure (preferred):

• Experience with healthcare datasets (claims, eligibility, prior authorization, provider directories)
• Understanding of clinical or operational workflows (provider calls, documentation, adjudication steps)
• Awareness of healthcare data sensitivity and HIPAAlike compliance expectations