Generative AI Consultant

Key Responsibilities :

- Architect and implement LLM-based agent frameworks to support task automation and intelligent decision-making.

- Develop and optimize RAG (Retrieval-Augmented Generation) systems using efficient chunking strategies for context-aware responses.

- Use LangChain to orchestrate modular GenAI workflows integrated with vector databases (e.g., FAISS, Pinecone, Chroma).

- Build and maintain knowledge graphs and incorporate Vision APIs for multimodal intelligence.

- Apply advanced prompt engineering and token management to control costs and improve LLM accuracy.

- Ensure reliability and robustness through hallucination control methodologies and responsible AI practices.

- Design and deploy scalable GenAI applications on cloud platforms (Azure, AWS, or GCP).

- Collaborate with cross-functional teams including data scientists, cloud engineers, and domain experts to integrate GenAI into products.

- Leverage tools like Docker for containerization and Git for code versioning.

- Use SQL and Python to process and manipulate data effectively.

Must-Have Skills :

- Agent Frameworks (e.g., LangChain Agents)

- Retrieval-Augmented Generation (RAG)

- Chunking Strategies for document processing

- Deep understanding of LLMs (e.g., OpenAI, Anthropic, Meta, Cohere)

- Experience with AI services on Azure, AWS, or GCP (at least one)

- LangChain framework

- Vector Databases (e.g., FAISS, Pinecone, Weaviate)

- Token Management strategies

- Knowledge Graphs (e.g., Neo4j, RDF-based models)

- Vision APIs (e.g., Google Vision, AWS Rekognition, Azure Computer Vision)

- Prompt Engineering expertise

- Proficiency in Python

Good-to-Have Skills :

- AI/ML Algorithms and optimization

- Deep Learning frameworks (e.g., PyTorch, TensorFlow)

- Computer Vision models and techniques

- Hallucination Control Techniques

- Responsible AI frameworks and compliance methodologies

Technical Proficiency :

- Programming : Python (mandatory)

- Cloud : Azure, AWS, or GCP (at least one is mandatory)

- Containers : Docker

- Database : SQL

- Version Control : Git or similar

Qualifications :

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

- Relevant certifications in AI/ML or Cloud Platforms are a plus.

- Strong analytical thinking, problem-solving, and communication skills.