- Develop and maintain APIs (REST/gRPC) with clear versioning, backward compatibility, and OpenAPI/IDL specifications.

- Create and support CLIs and developer tools to simplify onboarding, testing, and deployment for internal and external users.

- Integrate features end to end : wire backend services to UI components, ensure consistent UX for platform features, and ship production ready front end changes

- Implement SDKs and client libraries across languages, manage packaging, distribution, and semantic versioning.

- Build and operate data pipelines for ingestion, transformation, and feature preparation; ensure data quality, lineage, and monitoring.

- Collaborate with ML and DevOps teams to enable model training, serving, and lifecycle management; integrate with CI/CD and AIOps workflows.

- Ensure reliability and performance : write tests (unit, integration), benchmark services, and optimize latency and throughput.

- Document and evangelize APIs, SDKs, CLIs, and integration patterns; produce examples, tutorials, and SDK reference guides.

- Security and compliance : implement secure defaults, secrets handling, and input validation for APIs and SDKs.

- Continuous improvement : gather developer feedback, iterate on DX (developer experience), and reduce friction for platform consumers.

Education and Experience :

- Bachelors or master degree in Computer Science, Information Technology, Engineering, or equivalent

- 5+ years of experience in building backend services, SDKs, APIs, and data pipelines; experience with AI/ML platforms or MLOps is highly desirable.

- Proven track record shipping production SDKs or client libraries and maintaining public or internal APIs.

- Experience integrating backend services with modern front ends and shipping UI features.

- Hands on experience with data engineering tools and production data workflows

Required Skills and Expertise :

- Languages : Python; plus one or more of Go, Java, or TypeScript.

- API and SDK : REST, gRPC, OpenAPI; SDK design patterns; packaging and distribution (PyPI, npm).

- CLI development : experience building robust CLIs (e.g., Click, argparse, Cobra).

- Frontend integration : familiarity with React, Angular, or Vue for adding UI features and collaborating with frontend engineers.

- Data engineering : SQL, ETL patterns, Spark, Airflow, Kafka or other streaming systems, Parquet/Delta.

- Model serving and MLOps : exposure to model serving frameworks (Triton, TorchServe, KFServing) and model lifecycle concepts.

- Cloud and infra : AWS/GCP/Azure fundamentals; containerization with Docker; Kubernetes basics for deploying services.

- CI/CD and automation : Git, GitOps, Jenkins/GitHub Actions/GitLab CI, automated testing and release pipelines.

- Observability and testing : logging, metrics, tracing (Prometheus, Grafana, OpenTelemetry strong testing discipline.

- Security and reliability : secrets management, input validation, rate limiting, and API security best practices.

Soft skills : API design, clear technical writing, cross team collaboration, and product mindset.