Generative AI Engineer

Role Overview :

Looking for a Generative AI Specialist with 5-7 years of experience focusing on state-of-the-art generative AI technologies including large language models (LLMs) and agentic AI. The candidate will act as a technical mentor, engaging with clients to develop advanced generative solutions and mentor junior team members.

Key Responsibilities :

Architect, fine-tune, and deploy Generative AI and LLM-based solutions for diverse industries.

Lead development of RAG pipelines, multi-agent orchestration, and generative workflows for automation.

Collaborate with clients to define problem statements, data strategies, and AI integration approaches.

Design and execute rapid prototypes and POCs using transformer-based and diffusion-based architectures.

Mentor junior engineers on LLM fine-tuning, prompt engineering, and API-based integration.

Continuously evaluate and adopt emerging open-source frameworks and foundation models (e.g., Llama, Claude, Gemini, Mistral).

Drive MLOps integration for generative AI solutions ensuring scalability, reproducibility, and compliance.

Requirements :

5–7 years of overall AI experience, with at least 2–3 years dedicated to Generative AI and LLM-based systems.

Hands-on experience building RAG, conversational, or multi-agent-based AI architectures.

Expertise in fine-tuning, prompt optimization, and LLM orchestration.

Proven success in developing generative solutions for enterprise applications.

Excellent communication and technical mentoring skills.

Bachelor’s / master’s degree in computer science, AI, or related discipline

Desired Technical Skills & Tools :

Programming :

Python, LangChain, LlamaIndex, Multi Agentic Systems

LLM Frameworks :

OpenAI GPT series, Hugging Face Transformers, Anthropic Claude, Mistral, Llama 3, Agnos

Generative AI Tools :

LangGraph, Vector Databases (Pinecone, FAISS, Chroma), PromptLayer, LangFuse

RAG & Agent Frameworks :

Haystack, Semantic Kernel, AutoGen, CrewAI

MLOps & Deployment :

Docker, Kubernetes, MLflow, Vertex AI, Azure OpenAI, AWS Bedrock

Data & Integration :

REST APIs, Kafka, ElasticSearch, PostgreSQL, NoSQL, Data Lakes

Other Skills :

Prompt Engineering, Model Evaluation Metrics, Hallucination Control, Knowledge Graphs, Context Management

Cloud & Infra :

Azure AI Studio, AWS SageMaker, GCP GenAI Studio