IT Software Engineer (Data & AI Platform)

IT Software Engineer (Data & AI Platform)

• Location: Bangalore India

• Work Mode: Onsite

• Experience: 5 Years

• Open Positions: 1

The IT Software Engineer will contribute to building and scaling enterprise-grade Data & AI platforms. The role involves designing backend services APIs SDKs and data pipelines to support AI/ML workflows and analytics use cases. The position requires hands-on development system integration and collaboration across engineering data and DevOps teams.

• Design and develop platform components including core services SDKs and reusable modules

• Build and maintain APIs (REST/gRPC) with versioning and backward compatibility

• Develop CLI tools and developer utilities for platform usability

• Integrate backend services with frontend components and support UI feature delivery

• Implement SDKs and manage packaging and distribution (e.g. PyPI npm)

• Build and maintain data pipelines for ingestion transformation and feature engineering

• Ensure data quality lineage and monitoring across data workflows

• Collaborate with ML teams for model training serving and lifecycle integration

• Work with DevOps teams to integrate CI/CD and automation workflows

• Ensure system performance scalability and reliability through testing and optimization

• Implement logging monitoring and observability frameworks

• Follow security best practices including API security secrets management and validation

• Create technical documentation for APIs SDKs and developer tools

• Bachelors or Masters degree in Computer Science IT Engineering or related field

• 5 years of experience in backend development APIs SDKs and data engineering

• Experience in building production-grade systems and scalable services

• Exposure to AI/ML platforms or MLOps environments

Programming Languages:

• Python (mandatory)

• Go / Java / TypeScript (at least one)

API & SDK Development:

• REST gRPC OpenAPI specifications

• SDK design patterns and versioning

• Package management (PyPI npm)

Data Engineering:

• SQL ETL pipelines

• Apache Spark Airflow

• Kafka or streaming systems

• Data formats: Parquet Delta Lake

Frontend Integration:

• Basic understanding of React / Angular / Vue

MLOps & Model Serving:

• Exposure to Triton TorchServe KFServing

• Model lifecycle and deployment concepts

Cloud & Infrastructure:

• AWS / GCP / Azure fundamentals

• Docker Kubernetes

CI/CD & Automation:

• Git GitOps

• Jenkins / GitHub Actions / GitLab CI

Observability & Testing:

• Logging monitoring tracing (Prometheus Grafana OpenTelemetry)

• Unit and integration testing

Security & Reliability:

• API security input validation

• Secrets management rate limiting

• Python programming

• REST API development

• gRPC services

• SDK development and design patterns

• Data engineering (ETL pipelines SQL)

• Apache Spark / Airflow

• Kafka or streaming systems

• Docker and Kubernetes

• CI/CD pipelines (Jenkins / GitHub Actions / GitLab CI)

• API security and observability (Prometheus Grafana)