4 days ago
Hyderābād, IndiaMid Level / Senior
Responsibilities
- Design and develop production-grade AI and agentic platform services, APIs, and SDKs.
- Build reusable capabilities for AI agents, tools, skills, MCP integrations, and agent workflows.
- Develop Python-based solutions using AI frameworks such as LangChain, LangGraph, and Pydantic AI.
- Build durable distributed workflow orchestration for long-running AI and engineering workloads.
- Integrate AI workflows with job execution environments, source-control systems, engineering tools, and internal services.
- Develop CLI and developer tooling for installation, configuration, validation, updates, and integrations.
- Implement reliable execution patterns involving retries, failure handling, state management, and external-system interactions.
- Prototype rapidly and evolve successful prototypes into secure, maintainable, production-ready solutions.
- Create technical documentation, examples, and reference implementations for engineering teams.
- Translate complex engineering processes into reusable AI-enabled workflows with cross-functional domain teams.
- Develop distributed applications using service-oriented or microservices architectures, message queues or event-driven patterns, caching, idempotency, retries, and consistency-aware design.
Requirements
- Bachelor's degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or a related field; the posting also lists B.Tech/M.Tech in Computer Science, Electronics, or a related engineering discipline.
- 3–7 years of software engineering experience, including at least 3 years of Data Science or related work experience.
- Strong Python software engineering experience developing backend services and APIs.
- Hands-on experience developing Generative AI or LLM applications and production AI systems.
- Experience with agent or application frameworks such as LangChain, LangGraph, Pydantic AI, or equivalent technologies.
- Experience designing REST APIs, SDKs, or developer-facing libraries.
- Understanding of distributed systems, asynchronous processing, workflow execution, and failure and retry patterns.
- Experience integrating enterprise systems, developer tools, or engineering platforms.
- Experience with production observability, logging, telemetry, or tracing.
- Strong Elasticsearch experience, including mappings, analyzers, shards and replicas, aggregations, query DSL, index lifecycle management, performance tuning, and vector or hybrid search.
- Hands-on experience designing and operating RAG systems, including retrieval evaluation, relevance measurement, grounding quality, and hallucination mitigation.
- Advanced relevant degrees may substitute for up to two years of work experience, with a Master's substituting one year and a Doctorate substituting two years.
- Strong debugging, analytical problem-solving, technical communication, documentation, collaboration, and cross-functional delivery skills.
Tech Stack
ElasticsearchPython
Categories
About Qualcomm
Qualcomm is a public semiconductor company headquartered in San Diego, founded in 1985, that designs and sells wireless chipsets and platforms for mobile devices, automotive, IoT, and networking, notably the Snapdragon application processors and 5G modems. It also licenses a large portfolio of cellular patents to device makers, generating revenue alongside chip sales; its technology underpins many Android smartphones and emerging automotive and edge-compute systems, and it trades on NASDAQ as QCOM.