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    Job · 19914396

    Mphasis logo

    Production Support SRE with AI/ML

    Mphasis · Hyderabad · hybrid · Posted 21d ago

    Undisclosed8–13 yrsfulltimeSourced fromNaukri

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

    About this role

    Production Support SRE Engineer with AI/ML

    Hybrid (3 days from Office)

    Location: Hyderabad only (Need locals as there is 1 round of F2F)


    Years of exp: 10+ yrs

    Primary: Production Support Engineering, Site Reliability Engineering (SRE), GCP, AI/ML Platform

    Secondary skills: Python, Linux/Unix, GPU Infrastructure, GenAI Support, Splunk, AppDynamics, Hadoop/Spark, Automation Engineering

    Job Description:

    • Responsible for support functions and driving the execution of multiple Application/Platform support services including incident triage, root cause analysis, change evaluation-execution-validation,

    deployment management, BCP and risk & vulnerability management, patching, monitoring.

    • Provides on-call production support of Mission Critical applications and resolve issues within RTO.
    • Leverage diagnostic tools to maintain, troubleshoot and restore service or data to systems
    • Bring in engineering, operational management in various domains like AI & Cloud
    • Leverage AI-enabled applications, tools, Large Language Models (LLMs), Generative AI, Agentic AI frameworks, and Retrieval-Augmented Generation (RAG) architectures
    • Champion continuous improvement to drive stability and operational excellence
    • Work with SRE mindset. Building Automated solutions for daily redundant production support activities.
    • Ability to understand and escalate issues efficiently and appropriately. Identify system bottlenecks and opportunities for process improvements
    • Communicate, co-ordinate and collaborate with multiple support teams and stakeholders

    Required Qualifications:

    • Must have 12+ Years of Production Support experience
    • Proven experience implementing SRE processes in support teams
    • Experience supporting applications using Python stack
    • Knowledge and understanding of technology infrastructure: data center, network, storage, and compute domains.
    • Hands on experience on GCP with certification
    • hands-on experience in configuring, managing, and optimizing GPU-based infrastructure and environments for AI/ML workloads.
    • Proven expertise in diagnosing and resolving capacity, performance, and scalability issues associated with AI and machine learning workloads.
    • Strong experience troubleshooting, supporting, and resolving production issues in Generative AI (GenAI) applications and services.
    • Knowledge/experience of Python/Shell scripting.
    • Knowledge/ experience supporting Data Science/AI/ML platforms
    • Strong user/admin experience with Linux/Unix command line.
    • Exposure supporting with big data technologies such as Hadoop, Spark, elastic search etc
    • Strong experience with monitoring systems such as Splunk, App Dynamics.
    • Candidate should have experience in serving as a liaison between technology infrastructure operations and business projects.
    • Excellent verbal and written communication skills.
    • Exceptional problem solving and analytical skills.
    • Willing to work in shifts (24x7 models)

    Sourced from naukri

    Skills

    Aimlgoogle cloud platformSite Reliability EngineeringUnixPythonProduction SupportLinux

    About Mphasis

    Mphasis logo

    Mphasis

    IT Services & Consulting

    30.2k+

    employees

    1998

    28 years old

    Bangalore/Bengaluru, Karnataka

    India

    About

    At Mphasis, engineering is in our DNA. We lead with design and architecture to deliver a portfolio of next-gen offerings and services that blend our deep domain expertise with cutting-edge technology.

    Industries

    IT Services & ConsultingFinancial ServicesHardware & NetworkingInsuranceEmerging Technologies

    Employee ratings

    10,251 reviews

    3.3/ 5

    Culture

    3.2

    Career growth

    2.4

    Work-life

    3.5

    Employees rate it well for

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