Enterprise AI OS Architect (Forward‑Deployed)

Tata Communications Limited; Scotland; On-site; GBP 110,000 - 190,000; Full time

Job summary

Tata Communications Limited is seeking an AI OS Architect to turn complex customer operations into a clean ontological model, wire data and systems into it, and orchestrate LLM-driven agents and workflows with governance and cost discipline.

The role requires experience in deploying an enterprise AI platform, strong data engineering capabilities, and the ability to lead on-site customer engagements and design reusable architecture for multiple deployments.

Qualifications

• Must-have enterprise AI OS architecture experience with deployed platform
• Ontology-first thinking modelling enterprise objects, actions and processes
• Deep data engineering pipelines, lakehouse and data lineage
• LLM/agent orchestration, context engineering and tool use
• Enterprise governance, security IAM, and GDPR/SOC2 awareness
• Forward-deployed temperament: travel, ambiguity, client-facing

Responsibilities

• Define enterprise ontology and data architecture for reusable modelling
• Lead customer discovery and map objects, relationships, and processes
• Architect data foundations from ops systems to governed data layer with lineage
• Design reusable object/action/process models across AI workflows
• Architect AI platform, RAG, agent orchestration, and governance
• Lead 1-2 major customer engagements on-site through delivery and launch
• Develop quick, value-proving thin slices and capture field learnings for productFeedback

Skills

Enterprise AI OS architecture

Ontology-first modelling

Data pipelines & lakehouse

LLM orchestration & agents

Security & governance

Forward-deployed delivery

Executive-level communication

Tools

SQL

PySpark

Job description

Tata Communications Limited is seeking an AI OS Architect to turn complex customer operations into a clean ontological model, wire data and systems into it, and orchestrate LLM-driven agents and workflows with governance and cost discipline.

The role requires experience in deploying an enterprise AI platform, strong data engineering capabilities, and the ability to lead on-site customer engagements and design reusable architecture for multiple deployments.