- Design and deploy end-to-end generative AI solutions - from data ingestion and RAG pipelines to model serving, agent orchestration, and prompt engineering - in production environments.
- Build and optimize Python-based backend services using LangChain, LlamaIndex, and agent frameworks (e.g., AutoGen, CrewAI) for enterprise use cases.
- Integrate LLMs (OpenAI, Anthropic, Mistral, Llama 3, etc.) with enterprise systems (CRM, ERP, Knowledge Bases) via API gateways and vector DBs (Pinecone, Weaviate, FAISS).
- Collaborate with data scientists to fine-tune, evaluate, and deploy open-source LLMs on cloud platforms (AWS, Azure, GCP) using SageMaker, Vertex AI, or Azure ML.
- Implement observability, cost monitoring, and guardrails (safety, hallucination detection, rate limiting) for GenAI deployments.
- Mentor junior engineers, document architecture decisions, and enforce MLOps best practices (CI/CD, model versioning, drift detection).

Skills & Qualifications

- Must-Have
- Python
- LangChain




- LlamaIndex
- OpenAI API
- FAISS
- Pinecone
- Vector Databases
- LLM Fine-tuning
- RAG Architectures
- Agent Frameworks
- API Gateway Integration
- Cloud Platforms (AWS/Azure/GCP)
- Model Monitoring Tools
- CI/CD for ML

- Preferred
- AutoGen
- CrewAI
- MLflow

Benefits & Culture Highlights

- Work on bleeding-edge GenAI projects for global clients across healthcare, finance, and logistics.
- Flexible PTO, quarterly hackathons, and dedicated AI research time.
- Chance to publish whitepapers, speak at AI conferences, and influence enterprise AI roadmaps.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Gen AI Engineer (Gurugram)
🏢 Zorba AI
📍 Gurugram