🎁 Zanim zaaplikujesz, przećwicz tę rozmowę. Załóż darmowe konto WorkMundi i odbierz Trening rozmowy kwalifikacyjnej w HelpsYouSpeak — bez opłat, bez karty. Chcę swój trening →
About Us At Netwrix, our mission is to revolutionize data security by placing identity at the core - providing unparalleled visibility and control. Engineered and supported by over 900 highly talented, motivated employees and hundreds of trusted partners in nearly every geography, Netwrix solutions are relied upon daily by security professionals across more than 13,500 organizations in over 100 countries around the world. Over the past two decades, Netwrix has expanded its market presence through innovation, organic growth, and strategic acquisitions, and are proud to be backed by renowned private equity firms, TA Associates and Centerbridge Partners. Netwrix maintains a global presence, fostering a remote-first work environment while encouraging and facilitating frequent face-to-face interaction with colleagues, customers, and partners. Position Overview The AI Data Engineer designs, builds, and operates enterprise‑grade data and AI platforms using GitOps principles. This role combines data engineering, AI enablement, platform engineering and IT Operations, with a strong emphasis on stability and repeatability. This role directly supports and enables Netwrix products and internal platforms, ensuring that AI and data capabilities align with Netwrix’s security‑first, governance‑driven mission. The AI Data Engineer will work with data generated by or integrated into Netwrix solutions such as: Netwrix Data Security Platform components, including data access governance, data classification, auditing and identity‑centric security telemetry. Platform Governance products (Drata, Salesforce and NetSuite), which generate configuration, change, and audit data requiring structured ingestion and analysis. Identity, endpoint, and infrastructure security products (e.g., Active Directory security, endpoint protection, privileged access, configuration management). Internal AI Agents and Experience Platforms where data must be securely scoped, versioned and observable across multiple domains/tenants. Key Responsibilities GitOps‑Driven Platform & Pipeline Engineering (GitHub, Azure DevOps, Terraform) Design, build and operate data and AI platforms as code, using Git‑based workflows as the source of truth. Implement pull‑request‑driven change control, automated testing and CI/CD pipelines. Define and maintain Infrastructure‑as‑Code for data and AI systems to ensure consistency, traceability, and rollback capability. AI & ML Data Pipeline Engineering (Azure ML Feature Store, Databricks Feature Store) Design and maintain scalable ETL/ELT pipelines that support: AI/ML model training and retraining Feature engineering and feature stores Batch and near‑real‑time inference workflows Design pipelines backwards from business requirements while accounting for data freshness, latency and reliability. GenAI & RAG Enablement (Azure OpenAI and AI Search, internal Netwrix data sources; internal AI agents, secured APIs) Support Retrieval‑Augmented Generation (RAG) and internal AI agents by curating, indexing and refreshing select data sources. Build and operate pipelines for: Embedding generation and lifecycle management Vector database ingestion and maintenance Context retrieval and prompt‑adjacent data flows Data Quality, Governance & Observability (Azure Monitor, ML monitoring, Application Insights) Implement proactive monitoring for: Data quality and schema integrity Pipeline performance and failure modes Distribution shifts and data drift impacting AI systems Integrate security, privacy and compliance controls directly into pipelines by design. Must partner with both Product and Corporate Security teams. Maintain clear, auditable data lineage, ownership and documentation. MLOps & Production Readiness (Azure ML Model Registry, Runbooks, operational handoff documentation) Partner with Product and Engineering teams to operationalize models by: Integrating data pipelines into MLOps workflows Supporting model versioning, retraining and rollback strategies Enabling observability across data and model performance Ensure AI systems/integrations are supportable by IT Operations and Solutions team members; train or provide guidance at a regular cadence. Cloud & Platform Engineering (Azure Storage, Azure Kubernetes Service, Azure Container Registry) Build and operate Azure‑based data and AI platforms, including storage, compute, orchestration and containerized services. Optimize platforms for cost efficiency, performance, reliability and scale in a global, mostly remote work environment. Support hybrid or restricted environments where AI systems must meet enterprise or regulatory constraints. Cross‑Functional Collaboration Work closely with: IT Operations & Platform Engineering (Intune, Entra ID) Security & Governance teams (Netwrix, Drata) Data Science and AI Engineering (Azure ML, Azure OpenAI) Product and business stakeholders (Salesforce, NetSuite) Translate AI and business requirements into durable, enterprise‑ready architectures. Produce clear architecture diagrams, runbooks, and operational documentation. Required Qualifications Bachelor’s Degree in Computer Science, Data Engineering, Engineering, or equivalent practical experience. 5 - 7 years of experience in data engineering, platform engineering, or infrastructure roles. Strong proficiency in Python and SQL, with working fluency in JSON, YAML, and shell scripting. Experience using Gitbased workflows, Infrastructure as Code, and CI/CD pipelines to build and operate data and AI platforms in production environments. Experience operating workloads in Azure and AWS. Has performed direct and operational applications of large language models (LLMs) and GenAI platforms (OpenAI, Anthropic Claude, Google Gemini) within enterprise controlled environments. Our Values At Netwrix, Our Values Guide Every Action Next-Level Customer Focus -Customers first, always. We listen, protect, and go the extra mile— because their success is our mission. Excellence - We set high standards and take pride in delivering exceptional results. We celebrate wins, seek constant improvement, and address shortcomings professionally. Transparent Ownership - We celebrate our successes, own up to our mistakes, communicate openly, and face challenges head-on with a genuine commitment to doing the right thing. Winning with Clear Thinking - We value clarity, find straightforward solutions to complex problems, and make swift, effective decisions. Relentless Innovation - We continually seek better ways to serve our customers and stay ahead. We foster creative thinking, and we embrace new approaches. Industry-Leading Expertise - We take pride in our expertise and continuously seek to learn and share knowledge, striving to be the trusted experts our customers rely on. eXceptional Together - We believe in the power of collaboration and diverse perspectives. By valuing each other’s strengths, we achieve outcomes that surpass individual contributions. Join us in a culture where integrity, respect, and hard work are foundational. Be part of a team dedicated to making a lasting impact. Why You’ll Love Working at Netwrix Competitive Health Benefits Continuous Learning and Development Opportunities Team-Oriented, Collaborative, and Innovative Work Environment Regular Company Town Halls to Keep You Informed Opportunities for Career Growth and Advancement We pride ourselves on a culture that truly values employee input across various backgrounds and experiences. We look forward to welcoming new talent who can help us further our mission. Netwrix Corporation and its wholly owned subsidiaries are Equal Opportunity Employers (EEO) and welcome all applicants for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other protected characteristic under applicable law. Please let
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.