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    vega tech solutions private limited logo

    Director of Data & AI Engineering

    vega tech solutions private limited · Chennai · onsite · Posted 1d ago

    Not disclosedFresherfulltimeSourced fromFoundit

    About a minute. You'll make an account on the way through.

    About this role

    About The Opportunity

    We operate in the Enterprise Data & Artificial Intelligence sector, delivering production-grade ML, MLOps, and scalable data-platform solutions to enterprise customers across industries. This is a senior engineering leadership role for a hybrid-based team in India, responsible for building high-performance Data & AI engineering capabilities that convert advanced models into reliable, secure, and cost-effective production services.

    Role & Responsibilities

    • Define and execute the Data & AI engineering strategy and roadmap—align architecture, tooling, and delivery to business outcomes and go-to-market priorities.
    • Lead, hire, and scale cross-functional teams (ML engineers, data engineers, MLOps, SRE) to deliver production-grade ML and data platforms.
    • Architect and operationalize end-to-end ML systems: data ingestion, feature stores, training pipelines, model registry, serving, monitoring, and automated retraining.
    • Establish engineering best practices: CI/CD for ML, infrastructure as code, observability, security, cost controls, and incident management.
    • Partner with Product, Customer Success, and enterprise clients to translate use-cases into measurable KPIs and production SLAs; drive prioritization and delivery cadence.
    • Manage vendor relationships, procurement, budgets for cloud and third-party AI tooling; mentor senior managers and build a culture of technical excellence and ownership.

    Skills & Qualifications

    Must-Have

    • Proven track record leading engineering teams that built and operated production ML or data platforms at scale.
    • Deep technical understanding of ML lifecycle and MLOps—model training, deployment, monitoring, and drift management.
    • Hands-on experience designing cloud-native architectures and optimizing cloud cost/performance.
    • Strong stakeholder management—ability to translate business problems into technical roadmaps and measurable outcomes.
    • Experience implementing CI/CD, observability, and security practices for data and ML pipelines.
    • Demonstrated ability to recruit, mentor, and develop senior engineering managers and technical leaders.

    Preferred

    • Experience in a consulting or services environment delivering enterprise AI solutions.
    • Prior ownership of platform productization (APIs, SDKs, developer experience) for internal or external customers.
    • Advanced degree in Computer Science, Machine Learning, or related field (or equivalent industry experience).

    Benefits & Culture Highlights

    • Hybrid work model with flexible in-office days and a high-autonomy engineering culture.
    • Competitive compensation, performance-linked incentives, and opportunities for equity participation.
    • High-impact role: lead strategic initiatives, influence product direction, and mentor emerging leaders in a growth-focused environment.

    Location: Chennai, Hyderabad, Bangalore (Hybrid)

    We welcome senior engineering leaders who are passionate about turning ML research into reliable, production-quality systems. Apply to help shape the next generation of enterprise Data & AI platforms.

    Skills: cloud,enterprise,data engineering,llm,gen ai,python,rag,ml,data,artificial intelligence,platforms,data science,mlops,agentic ai,genai

    Sourced from foundit

    Skills

    observabilitydrift managementMLOpsdata platformsCloud-native architecturesModel Trainingsecurity practicesData EngineeringCi/CdMachine Learning

    About Vega Tech Solutions

    vega tech solutions private limited logo

    vega tech solutions private limited

    ₹3.1L PA avg

    Avg at Vega Tech Solutions

    Employee ratings

    4 reviews

    4.9/ 5

    Culture

    4.3

    Career growth

    3.8

    Work-life

    4.3

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