We are seeking an experienced Generative AI Engineer/Lead to design, architect, and deliver scalable AI-powered solutions leveraging Large Language Models (LLMs), Agentic AI frameworks, Retrieval-Augmented Generation (RAG), and cloud-native AI services. The ideal candidate will have deep expertise in AI/ML architecture, strong Python development skills, cloud technologies, and hands-on experience deploying enterprise-grade GenAI applications.

The role involves collaborating with business stakeholders, data scientists, engineering teams, and technology leadership to build creative AI solutions that drive business transformation.

Role & responsibilities

• Design and build LLM-powered applications using proprietary and open-source models.
• Implement prompt engineering, Retrieval-Augmented Generation (RAG), tool/function calling, and agent workflows.
• Deploy LLM solutions into cloud and enterprise settings with scalability and reliability.
• Build inference APIs, microservices, and CI/CD pipelines for AI applications.
• Monitor model quality, latency, cost, drift,



and hallucinations in production.
• Fine-tune and enhance models using parameter-effective techniques where required.
• Optimize inference performance using caching, batching, quantization, and prompt optimization.
• Ensure security, privacy, and responsible AI guardrails in all deployments.
• Collaborate with product, platform, and engineering teams to deliver enterprise AI solutions.

Required Skills:

Programming:
Python (Expert Level)
REST APIs
FastAPI / Flask

Generative AI
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Cloud (AWS/Azure)
Vector Databases
AI Agents / Agentic AI
Fine-Tuning & Model Evaluation
Model Serving & Inference Optimization

AI Frameworks:
LangChain
LangGraph
LlamaIndex
Semantic Kernel
CrewAI / AutoGen
Hugging Face Transformers

Preferred candidate profile
5 to 15 years of overall software or AI/ML engineering experience

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