6-10 years of relevant experience in Apps Development or systems analysis roleCore AI/ML Foundations
o 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
o Extensive hands-on experience with leading LLMs such as Google
Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various
other open-source LLMs.
o Critical Deep working knowledge and hands-on experience with
Retrieval-Augmented Generation (RAG) pipelines, including advanced
RAG techniques and their detailed implementation.
o Proven ability to build, tune, and deploy LLM-based applications using
platforms like Vertex AI, Hugging Face, etc.
o Expertise in developing robust prompt engineering strategies, prompt
tuning, and creating reusable prompt templates.
o Hands-on experience with agentic framework-based use case
implementation.
o Working knowledge of Guardrails and methodologies for assessing the
performance and safety of GenAI features.
Programming & Data Engineering
o 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.
o Proficiency in integrating generative AI with enterprise applications using
APIs, knowledge graphs, and orchestration tools.
o Hands-on experience with various vector databases (e.g., PG Vector,
Pinecone, Mongo Atlas, Neo4j) for efficient data storage and retrieval.
o Experience in dealing with large amounts of unstructured data and
designing solutions for high-throughput processing.
Deployment and amp; MLOps
o Critical Hands-on experience deploying GenAI-based models to
production environments.
o Strong understanding and practical experience with MLOps principles,
model evaluation, and establishing robust deployment pipelines.
o Strong expertise in CI/CD principles and tools (e.g., Jenkins, GitLab CI,
Azure DevOps, ArgoCD) for automated builds, testing, and deployments.
Cloud and amp; Containerization
o Proven experience with container orchestration platforms like OpenShift or
Kubernetes for deploying, managing, and scaling containerized
