• Architect and maintain reliable, versioned APIs with strong backward compatibility for internal and external integrations.

• Deliver scalable microservices and async systems designed for high throughput, low latency, and real-time streaming.

• Set engineering standards across API design, testing, documentation, and CI/CD automation.

• Guide backend and frontend teams by providing clear HLD/LLD artifacts, conducting peer reviews, and ensuring clean architecture adoption.

• Champion telemetry integrations—logging, metrics, and tracing—across services to enhance system observability and debuggability.

• Publish client SDKs, Postman collections, and developer-focused portals to ease service consumption and onboarding.

• Mentor engineers, drive architectural clarity, and align backend strategies with product vision.

• Collaborate with AI/ML teams to integrate agent orchestration frameworks and model-serving platforms.

Required Skills:

• Expertise in backend development using Python, FastAPI and/or TypeScript (Node.js).

• Proven experience defining API contracts using OpenAPI, Swagger, gRPC, and Postman, with a strong contract-first development mindset.

• Deep understanding of microservices, event-driven and asynchronous system design, leveraging Kafka, RabbitMQ, or similar message brokers.

• Mastery of asynchronous programming, multiprocessing, and real-time streaming via WebSockets, Kafka streams, or media pipelines.

• Practical experience with cloud-native development (AWS, GCP, Azure), including autoscaling, serverless, API gateways, and managed databases.

• Hands-on experience with API lifecycle management—authentication, versioning, rate limiting, and throttling.

• Proficient in Docker, Git-based version control, and container orchestration workflows.

• Deep commitment to automated testing strategies, including TDD/BDD, unit, integration, and contract testing.

• Strong command of CI/CD pipelines, environment promotion strategies, and infrastructure-as-code principles.

• Skilled at producing HLD/LLD documentation, UML/sequence diagrams, and applying relevant design patterns for system resilience and scalability.

• Ownership of software release cycles, ensuring zero-downtime deployments and rollback strategies.

Good to Have Skills:

• Exposure to LLM orchestration (LangChain, LlamaIndex), prompt engineering, and tool-calling frameworks.

• Experience with RAG architectures, vector DBs (Milvus, Pinecone, PGVector), and MLOps frameworks (NVIDIA Triton, KServe).

• Understanding of Model Context Protocol (MCP) and Agent-to-Agent toolkits for advanced agent workflows.

• Clinical/life sciences exposure, including FHIR, clinical systems integration, or healthcare data privacy standards.

• Strong UX awareness to influence AI-driven product design and user journeys.

• End-to-end experience architecting AI-powered applications with measurable impact.

What is in it for you:

• Be part of a team and company that has won NVIDIA's AI Services Partner of the Year three times in a row with an unparalleled track record of building production AI applications on DGX and Cloud GPUs.

• Strong peer learning which will accelerate your learning curve across Applied AI, GPU Computing and other softer aspects such as technical communication.

• Exposure to working with highly experienced AI leaders at Fortune 500 companies and innovative market disruptors looking to transform their business with Generative AI.

• Access to state-of-the-art GPU infrastructure on the cloud and on-premise.

• Be part of the fastest-growing AI-first digital transformation and engineering company in the world

Originally posted on Himalayas