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Tier-1 brand, generalist AI/ML title, mid-level experience, and broad toolset create high applicant competition.
ML engineering skills transfer across industries, but healthcare claims experience raises domain specificity.
Explicit 4+ years and mandatory GenAI, Python, CI/CD, and database expertise enforce high shortlisting strictness.
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Architect, develop, and deploy large-scale AI and data-driven applications using Python and generative AI frameworks, including agentic AI workflows and prompt engineering.
Lead the building and optimization of CI/CD pipelines for AI-powered claims testing automation and production deployments using DevOps tools like GitHub Actions and Jenkins.
Develop automated claims testing solutions leveraging AI and machine learning to validate claims workflows, enhance accuracy, and provide technical leadership and mentoring in claims testing automation.
Bachelor's degree (B.E, B.Tech, MCA) or equivalent in computer science, engineering, information technology, or related field.
Minimum 4 years of hands-on experience in Python software engineering focused on AI and data solutions.
Proficiency with generative AI frameworks (LLM orchestration, agentic AI, prompt engineering, RAG), database integrations (PostgreSQL, Oracle, Vector DBs such as ChromaDB), and DevOps tools (GitHub Actions, Jenkins, Airflow, CI/CD pipelines).
Work Experience Required: 4+ years in Python AI software engineering; Notice Period: Not explicitly mentioned in the JD.
Experienced technical leader with deep expertise in architecting scalable AI-driven applications and automating complex business workflows, especially in healthcare claims systems.
Comfortable working in cloud environments with Kubernetes, container orchestration, and modern DevOps pipelines for continuous integration and deployment.
Skilled in integrating cutting-edge generative AI technologies into enterprise systems to improve operational efficiency, test automation, and developer productivity.