Python Fullstack Developer

Description JOB RESPONSIBILITY Backend Engineering: Develop robust APIs and backend services for claims processing, eligibility checks, and other healthcare operations using RESTful standards.Design and Develop Scalable Solutions: Architect and implement cloud-native applications using Python, microservices, and Kubernetes for healthcare data processing and analytics.Data Engineering: Design and maintain data pipelines for structured and unstructured healthcare data using PostgreSQL, MongoDB, and cloud-native tools.Frontend Development: Collaborate with UI/UX teams to build responsive and intuitive interfaces using Angular or React for healthcare applications.Healthcare Domain Expertise: Apply deep understanding of US healthcare systems, including claims, EDI transactions, and payer-provider workflows, to guide technical decisions.Cross-functional Collaboration: Work closely with product managers, data scientists, and QA teams to deliver high-quality software aligned with business goals.Participate in code reviews, documentation, and knowledge sharing to maintain high engineering standards.Security and Compliance: Ensure solutions adhere to HIPAA and other healthcare compliance standards, with secure data handling and access controls.Performance Optimization: Monitor and optimize system performance, scalability, and reliability in production environments.Mentorship and Leadership: Guide junior engineers, conduct code reviews, and promote best practices in software development and AI engineering.Preferred Tech Stack Contributions: Contribute to projects using Go and TypeScript where applicable, especially in performance-critical or frontend-heavy modules.Stay updated with emerging AI trends and contribute to internal innovation and proof-of-concept initiatives. QUALIFICATION B.E/B.Tech in Computer Sciences, IT, Engineering EXPERIENCE 6 to 7 years of Programming experience SKILLS AND COMPETENCIES Technical Skills Advanced proficiency in Pythonwith expertise in building scalable microservices using RESTful (FastAPI, Snaic) with low latency.Expertise in containerization technologies (Docker, Kubernetes)Software Engineering & Development: Strong coding practices with Python, and experience in microservices, test-driven development, and concurrency.DevOps & Infrastructure: Experience with CI/CD pipelines (GitHub Actions, Jenkins), and container orchestration (Kubernetes).Cloud Optimization: Familiarity with deploying AI workloads on GCP or any other cloud platforms.Version control and experiment trackingusing Git, MLflow, and other MLOps tools for reproducibility and collaboration.Proficiency in scripting languages (Bash, PowerShell)Knowledge of agile methodologies Domain Expertise Healthcare AI Applications: Understanding of healthcare-specific data modalities, privacy constraints, and domain adaptation for clinical and operational use cases.Evaluation Methodologies: Proficiency in designing benchmarks, conducting human evaluations, and applying automated metrics for model performance and safety.Mathematical Foundations: Strong grasp of linear algebra, probability, optimization theory, and information theory relevant to deep learning and model design.Research Methodology: Experience in experimental design, reproducibility, statistical analysis, and peer-reviewed publication processes. Professional Competencies Strong problem-solving and analytical skills, with the ability to translate complex AI concepts into scalable engineering solutions.Ability to rapidly prototype and iterateon GenAI and LLM-based applications, balancing innovation with performance and reliability.Effective collaboration across cross-functional teams, including data scientists, researchers, and product stakeholders, to deliver impactful AI solutions.Clear and concise communication skills, capable of presenting technical ideas to both technical and non-technical audiences.Commitment to engineering excellence, including writing clean, maintainable code, conducting thorough code reviews, and following best practices in software development.Proactive learning mindset, staying current with emerging trends in AI, GenAI, and agentic systems, and applying them to real-world problems.Experience in mentoring and knowledge sharing, supporting junior engineers and contributing to team growth and capability building.Ownership and accountabilityin delivering high-quality solutions under tight deadlines and evolving requirements.Focus on reproducibility and reliability, using tools like Git, MLflow, and CI/CD pipelines to ens .