Responsibilities

- Design, develop, and maintain Python backend services and REST APIs using FastAPI.
- Build modular, testable microservices, reusable platform components, and asynchronous or concurrent processing systems.
- Design data-access layers for PostgreSQL and MySQL, including schemas, transactions, indexes, and query optimization.
- Build event-driven integrations using Kafka or comparable messaging technologies.
- Containerize, deploy, configure, and troubleshoot services with Docker and Kubernetes.
- Contribute to CI/CD pipelines, automated quality checks, secure configuration, and repeatable deployments.
- Create unit and integration tests with Pytest and maintain engineering quality through peer review and documentation.
- Implement observability using structured logs, metrics, traces, health checks, and actionable alerts.
- Diagnose production issues, perform root-cause analysis, and deliver durable fixes.
- Integrate LLM APIs into enterprise services for GenAI, RAG, and agentic AI use cases where appropriate.
- Participate in technical design discussions and support less-experienced engineers through reviews and knowledge sharing.

Requirements

- Requires 3–6 years of hands-on software engineering experience, including robust recent experience building production Python backend services.
- Requires strong Python fundamentals,



object-oriented programming, data structures, error handling, packaging, and dependency management.
- Requires hands-on FastAPI and REST API experience, including validation, authentication, versioning, and error contracts.
- Requires knowledge of asynchronous programming, concurrency, and background-processing patterns.
- Requires practical PostgreSQL or MySQL experience and understanding of relational data modeling and performance fundamentals.
- Requires experience writing unit and integration tests with Pytest and applying mocking appropriately.
- Requires experience with Git, pull requests, code review, CI/CD, and automated code-quality practices.
- Requires hands-on Docker and Kubernetes experience, including deployments, services, configuration, secrets, health probes, and troubleshooting.
- Desirable qualifications include experience integrating Generative AI or LLM APIs into production applications.
- Desirable qualifications include understanding of Retrieval-Augmented Generation, agentic AI workflows, knowledge graphs, or graph-enhanced retrieval.
- Exposure to Redis, Celery, Helm, Kubernetes observability ecosystems, telecoms, network assurance, or high-availability enterprise environments is desirable.

📌 Software Engineering Professional (Bengaluru)
🏢 BT
📍 Bengaluru