Manager - Customer Interaction Suite

Role overview

Enterprise ontology and data architecture

• Map enterprise objects, relationships, actions, and processes into a shared, reusable ontology.
• Build governed data foundations and pipelines from operational systems, ERP/CRM, telemetry, documents, and knowledge bases.
• Design reusable data models with lineage, quality rules, access controls, permissions, and versioning.

AI platform and delivery

• Design RAG, context engineering, LLM and agent orchestration, tool calling, human-in-the-loop fallbacks, and evaluation loops.
• Architect autonomous, supervised, and human-in-the-loop agentic workflows.
• Own model selection, cost controls, prompt and version control, guardrails, safety and bias checks, drift monitoring, and audit trails.
• Lead customer engagements, run design workshops, build reference architectures, and support launches on site.
• Build an early proof of value and expand it; share field learnings with product and portfolio teams.

Must-have qualifications

• At least 8 years of experience, including mandatory relevant AI platform architecture experience.
• Must have architected and shipped an enterprise AI platform deployment in a forward-deployed, embedded, or equivalent setting.
• Generic ML or data science experience without enterprise deployment depth is insufficient.
• Demonstrated ontology-first modeling of enterprise objects, actions, and processes with consistent metadata, permissions, and data structures.
• Deep data engineering skills across pipelines, lakehouse or data platforms, streaming and batch, data quality and lineage, and zero-copy patterns.
• Fluency in SQL, PySpark, or equivalent.
• Hands-on depth with RAG, context engineering, prompt and agent orchestration, tool use, evaluations, guardrails, and cost or latency tuning; hands-on with at least one major LLM stack.
• Governance and security knowledge including IAM, row- or object-level permissions, model governance, and compliance awareness.

Locations and travel

• The posting lists India locations in Mumbai, Pune, Bengaluru, and Gurugram; London in the UK; and New York/New Jersey, Dallas, or remote within the US.
• Travel is up to 40–50%; customer-site stays are expected during major domestic and international deployments.