Tata Consultancy Services
Website:
tcs.com
Job details:
Role Purpose
Act as a technical authority for designing, building, and scaling enterprise‑grade AI solutions
Anchor complex AI programs beyond PoCs, driving reliability, scale, and business impact
Key Responsibilities
Architect and deliver production‑ready AI / GenAI / Agentic AI systems
Own end‑to‑end AI solutioning: problem framing, data strategy, model approach, deployment architecture
Drive industrialization of AI (scalability, performance, cost, governance)
Lead technical design reviews and resolve complex AI engineering challenges
Mentor senior engineers and define AI engineering standards and patterns
Partner with business and domain leaders to translate strategic problems into AI‑first solutions
Core AI & GenAI Expertise
Deep hands‑on experience with machine learning and modern GenAI techniques
Strong understanding of LLM‑based systems (prompting strategies, RAG patterns, orchestration, evaluation)
Experience with agentic or autonomous AI workflows is a strong advantage
Ability to evaluate trade‑offs across accuracy, latency, cost, and maintainability
Python Expertise (AI / Data Science – Expert Level)
Expert‑level Python for AI and data science workloads
Advanced use of Pandas and NumPy for large‑scale data preparation and feature engineering
Ability to write clean, scalable, production‑quality Python code (modular design, appropriate OOP, performance awareness)
Support end‑to‑end AI workflows using Python (data prep, training/evaluation hooks, inference pipelines)
Use visualization and diagnostics (e.g., Matplotlib or similar) to validate data and model behavior
Strong discipline in engineering hygiene (Git, environments, reproducibility, reviewable code)
Data & Platform Experience
Strong experience with data engineering and data platforms (pipelines, storage, transformations)
Hands‑on exposure to cloud‑based AI and data platforms (Azure, AWS, GCP, Databricks, Snowflake, etc.)
Familiarity with MLOps / LLMOps concepts
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