1 month ago
Gurgaon, IndiaStaff+
Responsibilities
- Build and ship LLM-powered features in a production application used at scale.
- Develop backend services and REST APIs using Python and related frameworks.
- Design and implement LLM systems including retrieval-augmented generation, agents, evaluation, semantic search, vector databases, and chunking strategies.
- Build, deploy, and secure MCP servers at scale.
- Use AI-assisted and agentic coding tools to write and refactor code, automate workflows, and optimize engineering processes.
- Own features and projects end to end, including planning, implementation, debugging, optimization, and delivery.
- Collaborate with Product Owners, global development teams, and cross-functional stakeholders.
- Apply data-driven, systems-level thinking to complex backend and AI engineering challenges.
Requirements
- At least 2 years of experience developing and experimenting with LLMs.
- At least 8 years of experience developing APIs with Python.
- Daily hands-on experience with AI-assisted and agentic coding tools such as Claude Code, Cursor, GitHub Copilot, or autonomous coding agents.
- Strong Python experience, particularly building REST APIs with frameworks such as FastAPI.
- Grounding in NLP and machine learning for building LLM systems.
- Experience with OpenAI and Anthropic model APIs.
- Experience building, deploying, and securing MCP servers at scale.
- Understanding of multi-agent systems and their applications.
- Experience designing and implementing end-to-end RAG systems, including vector databases, semantic search, retrieval quality, and chunking strategies.
- Experience with Elasticsearch, OpenSearch, or Solr for distributed search and indexing.
- Experience with prompt writing, Java or agentic coding in Java, and generative solutions deployed to production at scale.
- Proficiency with server-sent events, event-driven architectures, and messaging systems.
- Strong critical-thinking and systems-thinking skills, including debugging and optimizing complex backend systems.
- Understanding of backend security best practices, authentication, and data protection.
- Preferred experience with LLM guardrails, LangChain, LlamaIndex, LLM monitoring, observability, and LLM evaluation systems.
- Experience developing AI/ML technologies for large, business-critical applications is preferred.
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