Description

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 contemporary 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.

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.

📌 GEN AI Engineer (India)
🏢 Zensar Technologies
📍 India