- Design, develop, and deploy Generative AI and Agentic AI solutions for enterprise use cases.

- Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and knowledge retrieval systems.

- Develop intelligent AI agents and multi-agent systems using frameworks such as LangChain, LangGraph, CrewAI, LlamaIndex, NeMo Agent Toolkit (NAT), and related technologies.

- Implement and fine-tune Large Language Models (LLMs) and multimodal AI models for various business applications.

- Create effective prompts, prompt chains, and prompt optimization strategies to improve model performance and reliability.

- Develop end-to-end AI/ML solutions involving NLP, deep learning, predictive analytics, and automation workflows.

- Build scalable APIs and AI services for model inference and integration with enterprise applications.

- Perform model evaluation, testing, monitoring, and optimization to ensure high accuracy and efficiency.

- Collaborate with cross-functional teams including Data Scientists, Product Managers, Architects, and DevOps teams to deliver AI-driven solutions.

- Deploy AI workloads on cloud environments and implement MLOps best practices.

- Stay updated with emerging trends in Generative AI, Agentic AI, LLMs, and AI infrastructure technologies.

Required Technical Skills :

Generative AI & Agentic AI :

- Strong experience in Generative AI application development.

- Hands-on experience with :

1. Retrieval-Augmented Generation (RAG)

2. Prompt Engineering

3. AI Agents and Multi-Agent Systems

4. Knowledge Retrieval Systems

5. Conversational AI Applications

AI/ML & Deep Learning :

- Strong understanding of :

1. Machine Learning

2. Deep Learning

3. Natural Language Processing (NLP)

4. Large Language Models (LLMs)

5. Multimodal AI Models

- Experience with :

1. Transformers

2. CNN (Convolutional Neural Networks)

3. RNN (Recurrent Neural Networks)

4. Fine-tuning and Model Optimization Techniques

LLMs & Foundation Models :

- Hands-on experience with one or more of the following :

1. GPT Models

2. LLaMA

3. Mistral

4. Qwen

5. Nemotron

6. Other Open-Source Foundation Models

GenAI Frameworks :

- Experience with :

1. LangChain

2. LlamaIndex

3. LangGraph

4. CrewAI

5. NeMo Agent Toolkit (NAT)

6. NVIDIA NeMo Framework

Programming & Data Science :

- Strong proficiency in Python programming.

- Experience with :

1. Pandas

2. NumPy

3. TensorFlow

4. Keras

5. PyTorch

- Knowledge of software design principles and coding best practices.

Cloud & DevOps :

- Hands-on experience with one or more cloud platforms :

1. Microsoft Azure

2. Amazon Web Services (AWS)

3. Google Cloud Platform (GCP)

- Experience with:

1. Docker

2. Kubernetes

3. Git/GitHub/GitLab

4. CI/CD Pipelines

5. MLOps Concepts

Operating Systems :

- Experience working in Linux and Windows environments.

Desired Qualifications :

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

- Relevant certifications in AI/ML, Cloud Technologies, or Generative AI are preferred.

- Experience working on enterprise-scale AI applications is highly desirable