Backend Engineer – Generative AI
2 days ago
Role:
Backend Engineer – Generative AI & Agentic Systems (Python | LLMs)
Role Description: We're evolving to integrate LLM-based intelligence into our ecosystem and looking for a
Python Backend Engineer with expertise in building Agentic AI systems, LLM integrations, and context-aware RAG pipelines. This is a hands-on, full-time opportunity to help shape the next generation of intelligent, secure, cloud-native applications.
Work Location: Preference Bangalore (2025 will be remote work model, next year will be hybrid @ Bangalore office location)
Relevant Exp range: Junior: 2-3 years, Mid-Level: 3-5 years, Senior: 5-8 years
Mandatory Requirements
- 3–8 years of strong backend development experience using Python (NLTK, Spacy, FastAPI, Tensorflow, Keras, Pytorch, FastMCP, Pandas).
- Deep experience in REST API development, backend microservices, and production ready codebases.
- Experience working with SQL and understanding data modeling across both SQL (e.g., PostgreSQL) and NoSQL systems.
- Proficient in writing unit tests, debugging, documenting, and collaborating through code reviews.
- Comfortable with Docker, Kubernetes, and CI/CD pipelines.
- Familiarity with software patterns for high-performance, scalable AI services.
Specialization in GenAI, LLMs & Agentic Systems:
You have practical experience with LLM ecosystems and frameworks like:
- Langchain, LangGraph, CrewAI, Agnos, AutoGPT, or Semantic Kernel
- Experience building Retrieval-Augmented Generation (RAG) pipelines with:
- Vector stores (e.g., Chroma, Qdrant, Pinecone)
- Embedding models, chunking, and token window optimization
- Familiarity with Model Context Protocol (MCP) or other advanced context injection strategies
- Integrating with OpenAI, Anthropic, Ollama, Hugging Face, etc.
- Writing or using custom tools, memory components, or agent planners
- Designing multi-agent architectures or orchestrated workflows
- Working with prompt engineering, tool calling, and external APIs
Bonus Skills:
- Hands-on experience with federated query tools like Trino or Athena
- Familiarity with cloud-native deployments (GCP/GKE, AWS/EKS)
- Experience building data connectors (SQL/GraphQL APIs for RAG)
- Background in privacy-aware computing, data security, or compliance-driven design
- Any experience with Golang for microservices or infra tooling is a plus
What you will bring:
- Strong curiosity and an experimental mindset to explore fast-evolving AI tech
- Ability to prototype quickly but build robustly for production
- Startup mentality – autonomy, ownership, and deep collaboration with the team
- Desire to work on meaningful AI-powered solutions, not just LLM wrappers
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