AI Factory (MLOps, GenOps)

Department Icon Data Science Analytics & Machine Learning
149+ Applicants
Posted: 6 months ago
0-1 years
Bengaluru / Bangalore, Karnataka
work from office

Posted: 6 months ago
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Applicants: 150+
Job Description
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Job Description

Locations: Bangalore (Whitefield) / Pune (Talawade) / Chennai (Siruseri) / Mumbai (Airoli West)
Availability: Immediate candidates preferred

Role Overview:
This role will lead the design and implementation of an AI Factory platform to streamline development, deployment, monitoring and reuse of AI/ML & GenAI assets. The architect will define scalable MLOps + GenOps practices, build reusable components, standardize pipelines, and support cross-industry AI solutioning for pre-sales, PoCs, accelerators and delivery.

Key Responsibilities:

  • Architect and build an AI Factory repository of reusable models, prompts, agents, APIs and accelerators

  • Define and implement MLOps workflows (model development, deployment, CI/CD, governance)

  • Design GenOps pipelines (prompt engineering, LLM orchestration, evaluation, optimization)

  • Create blueprints/templates for standardized AI solution delivery across cloud platforms

  • Build accelerators for common use cases (chatbots, doc intelligence, summarization)

  • Support pre-sales, demos, RFP/RFI responses and technical strategy

  • Work with data engineering, DevOps, cloud and security teams

Required Skills:

  • Deep experience in MLOps tools: MLflow / Kubeflow / SageMaker / Azure ML / Vertex Pipelines

  • Knowledge of GenOps frameworks: LangChain, LlamaIndex, Semantic Kernel, TruLens, Ragas

  • Strong Python, YAML/JSON and API integrations

  • Experience with CI/CD pipelines (GitHub Actions, Jenkins, Azure DevOps), Docker, Kubernetes

  • Knowledge of model registries, observability, drift detection, auto retraining

  • Ability to build architecture docs & PPT decks

Preferred Qualifications:

  • Experience building an enterprise AI marketplace / model catalog

  • Looking to get Placed? Try our Placement Guarantee Plan

    Familiarity with LLMOps tools like W&B, PromptLayer, Arize AI

  • Cloud certifications (AWS/Azure/GCP)

  • Multi-cloud / hybrid AI deployment experience

Soft Skills:

  • Strong leadership & mentoring

  • Excellent communication & storytelling

  • Innovation mindset and fast execution capability

  • Comfortable in fast-paced, cross-functional environment

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Skills

PythonImplementationAi/mlPrompt EngineeringAiMl

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Important dates & deadlines?

Application Deadline

21 Dec 25, 04:35 PM IST

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AI Factory (MLOps, GenOps)

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