GEN AI Engineer

Job Summary

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.

Responsibilities

Key Responsibilities

• 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

Qualifications

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.

Nice to Have

• 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.