Gen AI

2 days ago

Bengaluru, Karnataka, India CrossAsyst Full time ₹ 5,00,000 - ₹ 8,00,000 per year

Position: Gen AI - Senior Developer

Experience: 4+ years

Locations: Bangalore/Pune/Hyderabad/Noida [Mode - Hybrid (2 days a week from office is mandatory)]

Job Description: We are seeking a skilled Gen AI - Senior Developer with a strong foundation in backend engineering and hands-on experience in Generative AI. The ideal candidate will have at least 3+ years of core Python development and 1–1.5 years of experience building and deploying

AI-powered applications. This role is best suited for individuals who enjoy developing scalable AI-driven services, writing production-grade code, and collaborating with cross functional teams to deliver enterprise-ready AI solutions.

Primary Responsibilities:

  • Develop and maintain Python-based microservices integrating Generative AIcapabilities
  • Build and optimize GenAI-powered solutions using Retrieval-Augmented Generation (RAG) pipelines and LLM orchestration tools
  • Implement RESTful APIs and backend services using FastAPI/Flask integrated with OpenAI, Azure OpenAI, or open-source LLMs
  • Collaborate with DevOps engineers to support CI/CD, containerization, and monitoring for GenAI pipelines
  • Work with ML engineers and data scientists to optimize AI models for performance and scalability
  • Participate in design discussions, contribute to code reviews, and ensure adherence to engineering best practices
  • Experiment with agentic workflows using frameworks such as LangChain, LangGraph, or Semantic Kernel

Core Skills Required:

  • Strong proficiency in Python development with experience in frameworks like FastAPI, Flask, and asyncio
  • Good understanding of microservices architecture and distributed systems
  • Hands-on experience with GenAI frameworks: LangChain, LlamaIndex, Hugging Face Transformers
  • Exposure to cloud platforms, preferably Azure (Azure OpenAI), for deploying LLM based services
  • Experience with REST API design and external service integration
  • Familiarity with vector databases such as FAISS, Pinecone, or Weaviate
  • Working knowledge of DevOps concepts (Docker, GitHub Actions, Kubernetes)

Secondary / Nice-to-Have Skills:

  • Exposure to agentic orchestration frameworks like Autogen, LangGraph, or Semantic Kernel
  • Experience with fine-tuning or customizing open-source LLMs
  • Understanding of observability, logging, and performance tuning in AI systems
  • Familiarity with MLOps practices and collaboration with ML/Data Science teams
  • Agile development experience with cross-functional engineering collaboration

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