Gen AI

Job Description

Role Name: Gen AI role 
6-10 years of relevant experience in Apps Development or systems analysis role 

•Core AI/ML Foundations: 
Strong foundational knowledge in GenAI, Machine Learning (ML modeling), 
Data Science, Statistics, and AI fundamentals, including Natural Language 
Processing (NLP), Neural Networks, and Large Language Models (LLMs). 
•Generative AI & LLM Expertise: 
Extensive hands-on experience with leading LLMs such as Google Gemini, 
OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-
source LLMs. 
Critical: Deep working knowledge and hands-on experience with Retrieval-
Augmented Generation (RAG) pipelines, including advanced RAG techniques 
and their detailed implementation. 
Proven ability to build, tune, and deploy LLM-based applications using platforms 
like Vertex AI, Hugging Face, etc. 
Expertise in developing robust prompt engineering strategies, prompt tuning, and 
creating reusable prompt templates. 
Hands-on experience with agentic framework-based use case implementation. 
Working knowledge of Guardrails and methodologies for assessing the 
performance and safety of GenAI features. 
•Programming & Data Engineering: 
Strong programming proficiency in Python is a must, including extensive 
experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, 
TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex. 
Proficiency in integrating generative AI with enterprise applications using APIs, 
knowledge graphs, and orchestration tools. 
Hands-on experience with various vector databases (e.g., PG Vector, Pinecone, 
Mongo Atlas, Neo4j) for efficient data storage and retrieval. 
Experience in dealing with large amounts of unstructured data and designing 
solutions for high-throughput processing. 

•Deployment & MLOps: 
Critical: Hands-on experience deploying GenAI-based models to production 
environments. 
Strong understanding and practical experience with MLOps principles, model 
evaluation, and establishing robust deployment pipelines. 
Strong expertise in CI/CD principles and tools (e.g., Jenkins, GitLab CI, Azure 
DevOps, ArgoCD) for automated builds, testing, and deployments. 
•Cloud & Containerization: 
Proven experience with container orchestration platforms like OpenShift or 
Kubernetes for deploying, managing, and scaling containerized applications in a 
cloud-native environment. 
•Soft Skills: 
Strong problem-solving abilities, excellent collaboration skills for working 
effectively with cross-functional teams, and the capability to work independently 
on complex, ambiguous problems.