Gen AI

We are looking for a skilled Generative AI Engineer to design, develop, and deploy AI-powered applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and modern AI frameworks. The ideal candidate should have hands-on experience in building enterprise-grade Generative AI solutions and integrating them into business applications.

Design and develop Generative AI solutions using Large Language Models (LLMs).

Build AI-powered chatbots, virtual assistants, knowledge assistants, and document intelligence solutions.

Design and implement RAG (Retrieval-Augmented Generation) architectures.

Develop AI Agents and multi-agent workflows for enterprise use cases.

Integrate AI solutions with enterprise systems, APIs, and cloud services.

Fine-tune, evaluate, and optimize foundation models for business requirements.

Implement prompt engineering techniques to improve response quality and accuracy.

Work with vector databases and semantic search solutions.

Monitor model performance, latency, security, and scalability.

Collaborate with data scientists, architects, developers, and business stakeholders.

Ensure compliance with Responsible AI, security, and governance standards.

Required Skills

Programming

Strong proficiency in: Python

SQL

REST APIs

Git

Generative AI & LLMs

Hands-on experience with: OpenAI GPT Models

Azure OpenAI

Anthropic Claude

Google Gemini

Llama Models

Mistral Models

Strong understanding of: Prompt Engineering

Fine-Tuning

Embeddings

LLM Evaluation

Token Management

AI Frameworks

Experience with: LangChain

LangGraph

LlamaIndex

Semantic Kernel

CrewAI

AutoGen

RAG & Vector Databases

Experience building: RAG-Based Applications

Knowledge Search Platforms

Enterprise Copilots

Hands-on experience with: Pinecone

ChromaDB

Weaviate

FAISS

Azure AI Search

Cloud Technologies

Experience with: Microsoft Azure

AWS

Google Cloud Platform (GCP)

Exposure to: Azure AI Services

Azure Machine Learning

Azure OpenAI Service

AWS Bedrock

Vertex AI

Data & Integration

Experience with: Data Pipelines

ETL Processes

Structured and Unstructured Data Processing

API Integrations

Enterprise Data Platforms

Preferred Skills

Experience with Machine Learning and Deep Learning concepts.

Knowledge of MLOps tools such as MLflow, Kubeflow, or Azure ML.

Experience with Docker, Kubernetes, and CI/CD pipelines.

Understanding of AI Security, Responsible AI, and Model Governance.

Exposure to multimodal AI solutions involving text, image, audio, or video models.

Educational Qualification

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

Soft Skills

Strong analytical and problem-solving skills.

Excellent communication and stakeholder management abilities.

Ability to work independently and within Agile teams.

Strong collaboration and teamwork skills.

Continuous learning mindset with a passion for emerging AI technologies.

Microsoft Azure AI Engineer Associate Certification.

Experience building enterprise AI assistants and copilots.

Exposure to Retail, BFSI, Healthcare, Manufacturing, or E-commerce domains.

Experience with Agentic AI, Multi-Agent Systems, and Autonomous Workflows.

Contributions to open-source AI projects or published AI research.