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Principal Ai Engineering Lead (genai & Mlops) @ Kantar

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Kantar  Principal Ai Engineering Lead (genai & Mlops)

Job Description

Why this job is important

AI is moving quickly but building AI that people can trust and that works reliably at enterprise scale takes strong engineering discipline. In this role, youll help shape the future of our AIenabled enterprise platforms by bringing together AI engineering, software architecture, and data science to deliver systems that are scalable, secure, and responsibly designed. Youll focus on turning real business needs into robust products: from designing how AI is embedded into platforms, to ensuring performance, monitoring, and governance are built in from day one.

This is a principal individual-contributor role, leading through technical authority, design ownership, and mentoring rather than formal line management.

What youll be doing

  • Leading the design and delivery of AIenabled enterprise platforms, from early architecture through to production.
  • Building and improving applied AI solutions (including LLM-based patterns such as embeddings, retrieval approaches, and model tuning where appropriate). [Principal_...ad_AI_0426 | Word]
  • Setting engineering standards for MLOps: CI/CD, model deployment, monitoring, evaluation, and operational reliability.
  • Architecting secure, cloud-native services (microservices, APIs, messaging/event-driven patterns) that support AI workloads at scale.
  • Coaching engineers and collaborating across Engineering, Data Science, and Product to turn complex AI concepts into practical delivery plans.

The skills experience needed

  • Experience building, deploying, and maintaining machine learning and generative AI solutions (e.g., LLMs, embeddings, retrieval patterns, vector search, model finetuning).
  • Strong MLOps knowledge across continuous integration, deployment, monitoring, and evaluation of AI/ML models.
  • Experience with AI infrastructure (orchestration pipelines, GPU compute, model hosting services) and scalable AI data structures (including vector databases/semantic search).
  • Deep software engineering capability in .NET Core/C# and modern back-end engineering, with flexibility to work across languages such as Python, Go, or TypeScript.
  • Strong understanding of distributed systems, microservices, cloud-native patterns, and modern data stores (SQL and NoSQL).
  • Secure coding mindset with awareness of cybersecurity risks, particularly around AI and data privacy.
  • Proven technical leadership (principal engineer/tech lead/architect level), with a track record of mentoring and influencing engineering direction.

Job Classification

Industry: Film / Music / Entertainment
Functional Area / Department: Engineering - Software & QA
Role Category: Software Development
Role: Head - Engineering
Employement Type: Full time

Contact Details:

Company: Kantar
Location(s): Hyderabad

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Keyskills:   ai mlops python technical leadership llm machine learning cybersecurity nosql sql microservices back end software architecture data science distributed systems coaching data privacy software engineering typescript architecture

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