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GenAI MLOps Engineer - Database

NIQ Digital Purchases·Salary not specified

Primary stack

DockerKubernetesPythonNeo4jCI/CDBash

Nice to have's

AirflowPrefectAzure ML PipelinesSageMaker PipelinesVertex AI PipelinesGitHub ActionsAzure DevOpsJenkinsPrometheusGrafanaDatadogAzure MonitorAWS CloudWatchLangChainLangGraphLangfuseLlamaIndexSemantic KernelPineconeWeaviateAzure AI SearchOpenSearchChromaDBFAISSTerraformCloudFormationARM/Bicep Templates

Job description

About the Position

We are seeking a highly skilled GenAI MLOps Engineer to join our AI Engineering team. In this role, you will design, build, deploy, and operate the core infrastructure powering our Generative AI and Machine Learning solutions. You will collaborate closely with Data Scientists, AI Engineers, Platform Engineers, and Software Development teams to productionize LLM-based applications, automate workflows, optimize infrastructure, and ensure scalable, secure, and cost-effective AI operations.

Responsibilities

  • ML Pipeline Engineering & CI/CD

    • Design, build, and maintain end-to-end ML pipelines covering data ingestion, preprocessing, model training, evaluation, deployment, and monitoring.
    • Develop scalable workflow orchestration using tools such as Airflow, Prefect, Azure ML Pipelines, SageMaker Pipelines, and Vertex AI Pipelines.
    • Build and maintain automated CI/CD pipelines using GitHub Actions, Azure DevOps, and Jenkins.
    • Automate code quality checks, security scanning, testing, model validation, and deployment processes.
  • Model Deployment & Serving

    • Containerize AI/ML workloads using Docker.
    • Deploy and manage ML inference workloads on Kubernetes (AKS/EKS/GKE), serverless platforms, and cloud-native AI services.
    • Implement advanced deployment strategies including canary deployments, blue-green deployments, shadow deployments, and A/B testing.
    • Support deployment of LLMs, RAG systems, and AI agents into production environments.
  • Monitoring, Observability & Reliability

    • Implement observability for AI systems through logs, metrics, and distributed tracing.
    • Monitor model latency, throughput, cost utilization, token consumption, user traffic, and service availability.
    • Create dashboards and alerting frameworks using Prometheus, Grafana, Datadog, Azure Monitor, and AWS CloudWatch.
    • Detect and resolve model drift, data drift, performance degradation, and infrastructure incidents.
  • Cloud & Infrastructure Engineering

    • Operate and optimize AI workloads on at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud Platform.
    • Manage AI services such as Azure Databricks, Azure OpenAI, AWS SageMaker, Amazon Bedrock, and Vertex AI.
    • Build and maintain Infrastructure-as-Code using Terraform, CloudFormation, and ARM/Bicep Templates.
    • Provision and manage compute clusters, networking, storage, security controls, and managed AI services.
  • Generative AI Orchestration & Vector Search

    • Build and maintain GenAI workflows using frameworks such as LangChain, LangGraph, Langfuse, LlamaIndex, and Semantic Kernel.
    • Support Retrieval-Augmented Generation (RAG) architectures.
    • Develop and optimize embedding pipelines, vector database integrations, index refresh processes, and knowledge retrieval systems.
    • Work with vector databases including Pinecone, Weaviate, Azure AI Search, OpenSearch, ChromaDB, and FAISS.
  • Security, Governance & Compliance

    • Implement secure AI deployment practices.
    • Manage secrets and credentials using enterprise-grade security solutions.
    • Ensure compliance with organizational security, governance, and data privacy standards.
    • Apply role-based access control (RBAC), encryption, and audit logging practices.
    • Support Responsible AI and model governance initiatives.
  • Cost Optimization & Performance Engineering

    • Monitor cloud consumption and AI infrastructure costs.
    • Optimize GPU utilization, compute efficiency, model serving costs, token usage, and storage consumption.
    • Recommend architectural improvements that improve scalability and reduce operational expenses.
  • Cross-Functional Collaboration

    • Partner with Data Scientists and AI Engineers to productionize models.
    • Collaborate with Software Engineering teams to integrate AI services into products.
    • Participate in architectural reviews and technical design discussions.
    • Support incident management and operational excellence initiatives.
  • Documentation & Operational Excellence

    • Create and maintain architecture diagrams, technical documentation, runbooks, SOPs, deployment guides, and on-call support documentation.
    • Establish best practices for AI platform operations and reliability.

Requirements

  • 5+ years of experience in DevOps, Platform Engineering, SRE, or MLOps roles.
  • Minimum 3+ years supporting Machine Learning, Deep Learning, or AI production systems.
  • Proficient in Databases specially Graph Db like Neo4j, memgraph (NosQL and SQL).
  • Must be able to do Data Modelling.
  • Must know about Embeddings, Vector Database, Semantic Search.
  • Must have scripting and automation skills using Python, Golang, Bash, or similar languages.
  • Strong hands-on expertise with one major cloud platform (Azure, AWS, or GCP).
  • Experience deploying AI/ML workloads at scale.
  • Strong experience with Docker, Kubernetes, and container orchestration.
  • Proven expertise building CI/CD pipelines.
  • Hands-on experience with Infrastructure-as-Code tools.
  • Experience with monitoring and observability platforms.
  • Working knowledge of LLMs, prompt engineering, RAG architectures, vector databases, and GenAI orchestration frameworks.

Preferred Qualifications

  • Experience working with Azure OpenAI, Amazon Bedrock, or Vertex AI.
  • Hands-on experience supporting production LLM applications.
  • Familiarity with GPU infrastructure and optimization.
  • Experience with model evaluation frameworks and LLM observability tools.
  • Knowledge of Responsible AI, AI governance, and security best practices.
  • Relevant cloud certifications (Azure, AWS, or GCP) are a plus.

We Offer

  • Flexible working environment
  • Volunteer time off
  • LinkedIn Learning
  • Employee-Assistance-Program (EAP)

About the Company

NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights-delivered with advanced analytics through state-of-the-art platforms-NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population.

For more information, visit NIQ.com

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Our commitment to Diversity, Equity, and Inclusion

At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the Diversity and Inclusion page.

© NIQ Digital Purchases. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.

NIQ Digital PurchasesNIQ Digital Purchases is an easy-to-use ecommerce measurement solution that enables manufacturers (& retailers) to have the broadest view of the digital commerce landscape and shopping behavior based on real online transactions.By extracting data from the largest e-receipt consumer panel in Europe and the USA, Digital Purchases offers a blind-spot-free view on how products perform across all e-commerce channels, while also generating insights on shoppers and shopping behaviors so you can evaluate your performance, adapt, and react to market dynamics.About NielsenIQNielsenIQis the industry leader in global measurement and data analytics and the most trusted source for retail and consumer intelligence.We deliver the complete truth to retailers, manufacturers, and our partners through our comprehensive data sets and powerful insights. We enable businesses to make critical decisions confidently, accelerating growth and optimizing performance.Our 30,000 employees — based in over 100 countries — are talented, passionate, and unwavering in their commitment to helping clients achieve success.

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