IT Software Engineer (Data & AI Platform)
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Job Location:
Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
IT Software Engineer (Data & AI Platform)
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Location: Bangalore India
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Work Mode: Onsite
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Experience: 5 Years
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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.
Key Responsibilities-
Design and develop platform components including core services SDKs and reusable modules
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Build and maintain APIs (REST/gRPC) with versioning and backward compatibility
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Develop CLI tools and developer utilities for platform usability
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Integrate backend services with frontend components and support UI feature delivery
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Implement SDKs and manage packaging and distribution (e.g. PyPI npm)
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Build and maintain data pipelines for ingestion transformation and feature engineering
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Ensure data quality lineage and monitoring across data workflows
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Collaborate with ML teams for model training serving and lifecycle integration
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Work with DevOps teams to integrate CI/CD and automation workflows
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Ensure system performance scalability and reliability through testing and optimization
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Implement logging monitoring and observability frameworks
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Follow security best practices including API security secrets management and validation
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Create technical documentation for APIs SDKs and developer tools
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Bachelors or Masters degree in Computer Science IT Engineering or related field
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5 years of experience in backend development APIs SDKs and data engineering
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Experience in building production-grade systems and scalable services
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Exposure to AI/ML platforms or MLOps environments
Programming Languages:
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Python (mandatory)
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Go / Java / TypeScript (at least one)
API & SDK Development:
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REST gRPC OpenAPI specifications
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SDK design patterns and versioning
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Package management (PyPI npm)
Data Engineering:
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SQL ETL pipelines
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Apache Spark Airflow
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Kafka or streaming systems
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Data formats: Parquet Delta Lake
Frontend Integration:
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Basic understanding of React / Angular / Vue
MLOps & Model Serving:
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Exposure to Triton TorchServe KFServing
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Model lifecycle and deployment concepts
Cloud & Infrastructure:
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AWS / GCP / Azure fundamentals
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Docker Kubernetes
CI/CD & Automation:
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Git GitOps
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Jenkins / GitHub Actions / GitLab CI
Observability & Testing:
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Logging monitoring tracing (Prometheus Grafana OpenTelemetry)
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Unit and integration testing
Security & Reliability:
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API security input validation
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Secrets management rate limiting
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Python programming
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REST API development
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gRPC services
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SDK development and design patterns
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Data engineering (ETL pipelines SQL)
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Apache Spark / Airflow
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Kafka or streaming systems
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Docker and Kubernetes
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CI/CD pipelines (Jenkins / GitHub Actions / GitLab CI)
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API security and observability (Prometheus Grafana)
