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    Job · 21315269

    HYDERABAD · FULLTIME

    AI Engineering & Data Science Lead

    Lonza

    Lonza

    Hyderabad · onsite · Posted 4d ago

    Sourced fromNaukri
    Undisclosed6–9 yrsfulltimeHyderabad

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    Section · 01

    About this role

    Role Purpose
    An AI Engineering & Data Science lead is for an AI Engineering and Data Science capability within the Lonza AI Factory (LAIF), defining the engineering standards, reusable capabilities, and technical approaches required to build and scale AI solutions across Lonza.
    This role is responsible for shaping the AI intelligence layer, driving AI engineering excellence, and enabling the successful delivery of AI products through cross-functional Fusion Teams.
    The position ensures AI solutions are scalable, secure, compliant, and designed for enterprise-wide reuse and adoption.

    Key Responsibilities AI Engineering Strategy, Architecture & Reusable Capabilities
    • Define the AI engineering and data science strategy, architecture principles, and technical roadmap for the Lonza AI Factory.
    • Shape and evolve the AI intelligence layer, including reusable services, contextual frameworks, orchestration capabilities, agentic patterns, and shared AI services.
    • Establish engineering standards and reference architectures covering AI/ML development, evaluation, deployment, monitoring, and lifecycle management.
    • Own and continuously evolve the approved catalogue of AI models, algorithms, frameworks, tools, and reusable components.
    • Partner with DDAI, IT, and technology teams to define technical requirements and priorities for AI platform services.
    • Drive build-versus-buy-versus-partner decisions for AI technologies and continuously evaluate emerging technologies and market trends.
    AI Engineering & Data Science Delivery
    • Lead AI engineering and data science delivery for strategic AI products and business-critical use cases through cross-functional Fusion Teams.
    • Provide hands-on technical leadership for complex AI solutions, including Generative AI, Agentic AI, Machine Learning, and Advanced Analytics.
    • Drive the industrialization of AI solutions by transitioning initiatives from proof-of-concept and experimentation into enterprise-scale production deployments.
    • Establish robust evaluation, testing, validation, performance measurement, and continuous improvement frameworks for AI models and agents.
    • Promote the reuse of common AI capabilities, engineering patterns, and shared services to maximize efficiency and scalability across products.
    • Support AI Product Leads and Business Product Owners in translating business challenges into technically viable and impactful AI solutions.
    AI Lifecycle, Operations & Responsible Engineering
    • Define AI and Machine Learning engineering lifecycle standards in partnership with IT and DDAI, including deployment, observability, monitoring, versioning, model governance, and operational resilience.
    • Embed security, privacy, responsible AI principles, and regulatory requirements into engineering frameworks and development practices.
    • Establish technical controls for AI evaluation, traceability, explainability, human oversight, and evidence generation, particularly for regulated and GxP-relevant environments.
    • Collaborate with DDAI and IT teams on AI FinOps, observability, and consumption monitoring to ensure scalable, sustainable, and cost-effective AI operations.
    Team Leadership & Capability Building
    • Support, lead, and scale a high-performing AI Engineering and Data Science organization across multiple locations.
    • Foster a strong technical community across LAIF, DDAI, and business domains, encouraging knowledge sharing, engineering excellence, and reuse of best practices.
    • Coach, mentor, and develop AI Engineers and Data Scientists while establishing clear capability frameworks and technical career pathways.
    • Develop strategic relationships with external technology partners, research institutions, and specialist providers to accelerate Lonza s AI capabilities and innovation agenda.
    Key Requirements
    • Bachelors or masters degree in computer science, Artificial Intelligence, Data Science, Engineering, or a related discipline.
    • Extensive experience leading AI Engineering, Machine Learning, Data Science, or Advanced Analytics teams in a large-scale enterprise environment.
    • Deep expertise in Generative AI, Agentic AI, Machine Learning, MLOps, AI Platforms, and AI solution architecture.
    • Proven track record of delivering enterprise AI solutions from concept through production deployment and operationalization.
    • Strong understanding of AI governance, responsible AI, security, privacy, and compliance requirements within regulated industries.
    • Experience building and scaling global technical teams and driving organizational capability development.
    • Excellent stakeholder management and communication skills with the ability to influence senior leadership and cross-functional teams.
    • Experience working within life sciences, healthcare, biopharmaceutical, or similarly regulated industries is highly desirable.


    Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

    Sourced from naukri

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    Section · 02

    Skills

    AI evaluationai servicesai modelsai technologiesCapability Buildingai governanceAnalyticsCommunication SkillsAlgorithmsArchitectureAdvanced AnalyticscomplianceAi PlatformAi SolutionsArtificial Intelligence

    Section · Company

    About Lonza

    Lonza

    Lonza

    Pharma

    174

    employees

    1897

    129 years old

    Basel

    Switzerland

    About

    A prominent provider of healthcare solutions, focusing on innovative therapies for disease prevention and specialized ingredients for various industries.

    Industries

    PharmaChemicals / Agri InputsManufacturing

    Employee ratings

    36 reviews

    3.5/ 5

    Culture

    3.4

    Career growth

    2.5

    Work-life

    4.1

    Employees rate it well for

    Senior Management4Career Growth4Work Life Balance4

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