Key Responsibilities
- Design and implement AI-powered products using LLMs, RAG pipelines, and AI Agents.
- Build and optimize prompt engineering, retrieval systems, and vector database integrations.
- Develop and deploy scalable AI/ML models and agentic workflows.
- Establish evaluation frameworks to monitor model quality, reliability, and performance.
- Collaborate with product, engineering, and DevOps teams to deliver AI features end-to-end.
- Implement AI safety, governance, and security best practices.
- Drive innovation by evaluating emerging AI tools, models, and technologies.
Required Skills
- 6+ years of software engineering experience with 3+ years in AI/ML.
- Strong expertise in Python, LLMs (OpenAI, Anthropic, Gemini), and AI Agent frameworks (LangChain, LangGraph, CrewAI).
- Experience with RAG architectures, vector databases, and prompt engineering.
- Hands-on experience with model fine-tuning, deployment, and MLOps.
- Proficiency in React, APIs, SQL/NoSQL databases, Docker, Kubernetes, and Cloud platforms (AWS/GCP/Azure).
- Strong understanding of AI evaluation, monitoring, and production deployment.
Nice to Have
- Experience with multimodal AI models, knowledge graphs, or open-source AI projects.
- Familiarity with TensorRT, ONNX, or edge/on-prem model deployment.
Pay: Up to ₹3,500,000.00 per year
Experience:
- ML Engineer: 3 years (Preferred)
- AI Engineer: 6 years (Preferred)
- Python, LLMs: 3 years (Preferred)
Work Location: In person
