About the role

Job Description

General/Project Information

Position / Designation to fill: Data Science Off-shore Lead – Agentic AI & Applied ML Systems
No. of positions: 1
Assignment Location: Kolkata (Hybrid)
Justification for the vacancy: New position within Data Science competency
Project/Domain details:
- Agentic AI systems combining Agentic frameworks ML, LLMs, tools, and business logic
- AI systems supporting complex environments such as process, manufacturing, Life Sciences and enterprise platforms
Needed By Date (DD/MM/YY): 01-03-2026
Work from Home: N
Request raised by: Ashutosh Ranjan
Approved by BU Head: Koushik Basu (Y)

Scope of Work

Work as a deeply hands-on applied AI leader, partnering closely with business, engineering, and platform teams to design, build, and deploy agentic AI systems (using ADK, A2A, MCP, LangGraph, Deep Agents) using enterprise/private LLM and agentic frameworks that operate in production environments. This is not a research-only role and not a pure consulting role. You will build alongside teams, prototype rapidly, pressure-test ideas against real constraints, and evolve systems until they are robust enough to be relied upon in critical workflows.

Responsibilities

Act as a technical partner to stakeholders, understanding end-to-end workflows and identifying where AI can meaningfully augment or automate decisions.
Design and build agentic AI systems that combine Agentic framework, ML models, LLMs, tools, rules, and feedback loops.
Move AI solutions from “this could help” to “this is embedded in how work gets done.”
Develop AI systems that reason over heterogeneous data sources, interact with enterprise systems, and take context-aware actions.
Collaborate closely with engineering teams to ensure solutions are deployable, observable, auditable, and maintainable.
Identify real-world constraints—data quality, latency, trust, explainability, failure modes—and design systems that work despite them.
Help define evaluation frameworks for agentic systems beyond model accuracy (usefulness, reliability, adoption, impact).
Mentor team members in building production-grade AI systems, not just models.
Contribute reusable agent patterns, reference architectures, and internal accelerators.

Skills Required

Essential Skills (Must have)

Strong foundation in applied ML and AI systems, beyond standalone models.
Hands-on experience building end-to-end Agentic AI systems that run in production environments.
Experience designing agentic workflows involving planning, tool use, execution, and feedback loops.
Experience with LLMs, RAG, tool-calling, and multi-agent architectures such as ADK, A2A, MCP, Deep Agents.
Strong Python skills and experience with ML frameworks (scikit-learn, PyTorch/TensorFlow).
Ability to reason across data, software, and business constraints simultaneously.
Comfort working in ambiguous problem spaces and iterating toward clarity.
Strong communication skills and ability to earn trust with engineers and business stakeholders alike.

Additional Skills (Good to have)

Familiarity with data visualization tools (Power BI, Tableau).
Understanding of data engineering, ETL/ELT frameworks, and pipeline orchestration.
Cloud proficiency (AWS, Azure, GCP).
Exposure to optimization methods (linear programming, mixed-integer programming, simulation).

Other Information

Educational Qualifications: Bachelor’s/Master’s in Engineering, Computer Science, Data Science, Operations Research, or Applied Mathematics
Experience Level (Total): 5+
Experience Level (Must Have Skills): 5+

Requirement Fulfillment

HR Representative

Name: ___________________

Designation: ________________

Signature: _______________ Date: ______________________

*All fields are mandatory

Data Science Off-shore Lead – Agentic AI & Applied ML Systems