20 days ago
Bengaluru, IndiaSenior / Staff+
Responsibilities
- Build AI/ML and agentic AI solutions using Google Vertex AI on Google Cloud Platform.
- Develop applications with Google ADK, LangGraph, prompt engineering, RAG, knowledge graphs, semantic modeling, and vector databases.
- Implement LLM and agent evaluation, including trajectory and trace-based evaluation, tool-calling and planning metrics, Pass@k, and judge-based methodologies.
- Create AI guardrails, governance controls, model monitoring, evaluation gating, and responsible AI practices.
- Develop Python services and NLP pipelines using FastAPI, Pandas, NumPy, PyTest, OCR, NER, document classification, information extraction, embeddings, and semantic search.
- Implement fuzzy matching, record linkage, and entity resolution techniques.
- Deploy production AI applications using GKE, Cloud Run, Docker, Kubernetes, MLOps, and LLMOps practices.
- Implement RBAC, data redaction, PII detection and masking, secrets management, and AI security governance.
- Communicate with stakeholders, document technical solutions, and contribute to solution architecture.
Requirements
- 5–8 years of professional experience.
- Mandatory experience in generative AI.
- Experience building AI/ML solutions with Google Vertex AI and Google Cloud Platform.
- Hands-on experience with Google ADK, LangGraph, and agentic AI frameworks.
- Expertise in LLM and agent evaluation frameworks and methodologies.
- Experience with RAG, knowledge graphs, semantic modeling, vector databases, AI governance, and responsible AI.
- Strong Python development skills with FastAPI, Pandas, NumPy, PyTest, and API development.
- Experience with OCR and intelligent document processing using Google Document AI, Tesseract OCR, Azure Document Intelligence, or Amazon Textract.
- Experience with NER, document classification, information extraction, text preprocessing, tokenization, embeddings, semantic search, and NLP pipelines.
- Knowledge of machine learning, data science, statistical analysis, feature engineering, classification, regression, clustering, recommendation systems, and model evaluation metrics.
- Experience with AI evaluation and observability tools including Braintrust, Arize Phoenix, OpenTelemetry, Promptfoo, Galileo, DeepEval, Confident AI, Ragas, Langfuse, and LangSmith.
- Experience with GKE, Cloud Run, Docker, Kubernetes, cloud-native architectures, MLOps, LLMOps, and production AI deployment.
- Strong analytical, problem-solving, stakeholder communication, technical documentation, and solution architecture skills.
Tech Stack
Categories
About Wipro
Wipro is a global IT services and consulting firm that provides application development, cloud migration, infrastructure management, data/AI, and business process outsourcing for enterprises. It earns revenue through long-term outsourcing, managed services, and project-based consulting across multiple industries. Founded in 1945 and headquartered in Bangalore, India, Wipro is publicly traded (NYSE: WIT; NSE/BSE: WIPRO).