Principal, Agentic AI/Chatbots IC

5 - 10 years

14 - 18 Lacs

Posted:4 days ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Department Name: AI & Data Science

Role GCF: 6

ABOUT THE ROLE

Role Description:

We are seeking a Principal Machine Learning EngineerAmgens most senior individual-contributor authority on building and scaling end-to-end machine-learning and generative-AI solutions. Sitting at the intersection of engineering excellence and data-science enablement, you will develop, deploy and monitor modelsclassical ML, deep learning and LLMssecurely and cost-effectively. Acting as a player-coach, you will establishAIsolution strategy, define technical standards, and partner with DevOps, Security, Compliance and Product teams to deliver a frictionless, enterprise-grade AI solutions.

Roles & Responsibilities

  • Own enterprise AI/ML architecture, standards, APIs, and guardrails across cloud/on-prem.
  • Build production ML/GenAI solutions and lightweight apps delivering sub-second insights.
  • Build end-to-end ML pipelinesdata ingestion, feature engineering, training, hyper-parameter optimisation, evaluation, registration and automated promotionusing Kubeflow, SageMaker Pipelines, Open AI SDK or equivalent MLOps stacks.
  • Build and maintain full-stack AI applications by integrating model services with lightweight UI components, workflow engines or business-logic layers so insights reach users with sub-second latency.
  • Establish observability, SLOs, and safe deploys (blue-green/canary, shadow, rollbacks) with incident runbooks.
  • Lead rigorous evaluation (offline/online, A/B), drift detection, and automated retraining.
  • Architect LLM/RAG with prompt management, safety guardrails, and optimized inference.
  • Enforce data quality, lineage, and model/data cards; apply privacy-preserving techniques where needed.
  • Contribute reusable ML/GenAIcomponentsfeature stores, model registries, experiment-tracking librariesand evangelise best practices that raise engineering velocity across squads.
  • Perform exploratory data analysis and feature ideation on complex, high-dimensional datasets to inform algorithm selection and ensure model robustness.
  • Prototype and benchmark new algorithms, offering guidance on scalability trade-offs and production-readiness while co-owning model-performance KPIs.
  • Translate domain needs (R&D, Manufacturing, Commercial) into roadmaps; mentor teams and communicate trade-offs.

Must-Have

  • 5-7 years in AI/ML and enterprise software.
  • Strong command of machine-learning algorithmsregression, tree-based ensembles, clustering, dimensionality reduction, time-series models, deep-learning architectures (CNNs, RNNs, transformers) and modern LLM/RAG techniqueswith the judgment to choose, tune and operationalize the right method for a given business problem.
  • Proven track record selecting and integrating AI SaaS/PaaS offerings and building custom ML services at scale.
  • Expert knowledge of GenAI tooling: vector databases, RAG pipelines, prompt-engineering DSLs and agent frameworks (e.g., LangChain, LangGraph, Semantic Kernel).
  • Proficiency in Python and Java; containerization (Docker/K8s); cloud (AWS, Azure or GCP) and modern DevOps/MLOps (GitHub Actions, Bedrock/SageMaker Pipelines).
  • Strong business-case skillsable to model TCO vs. NPV and present trade-offs to executives.
  • Exceptional stakeholder management; can translate complex technical concepts into concise, outcome-oriented narratives.

Good-to-Have Skills:

  • Experience in Biotechnology or pharma industry is a big plus
  • Published thought-leadership or conference talks on enterprise GenAI adoption.
  • Masters degree in Computer Science and or Data Science
  • Familiarity with Agile methodologies and Scaled Agile Framework (SAFe) for project delivery.

Education and Professional Certifications

  • Masters degree with 12 -15 + years of experience in Computer Science, IT or related field

OR

  • Bachelors degree with 14 -16+ years of experience in Computer Science, IT or related field
  • Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus.

Soft Skills

  • Excellent analytical and troubleshooting skills.
  • Strong verbal and written communication skills
  • Ability to work effectively with global, virtual teams
  • High degree of initiative and self-motivation.
  • Ability to manage multiple priorities successfully.
  • Team-oriented, with a focus on achieving team goals.
  • Ability to learn quickly, be organized and detail oriented.
  • Strong presentation and public speaking skills.

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