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About the Role We are building an AI-native data platform that powers fraud detection and response across 360 Fraud Protection. We are hiring a Staff or Principal Data Engineer to own the data platform and data lake at the heart of that work. You work hands-on and own the domain end-to-end, alongside a small group of senior engineers, data scientists and product partners. Owns the unified data platform and data lake that powers detection and response across 360 Fraud Protection Every detection model and downstream AI capability depends on this data foundation, which makes it one of the highest-leverage engineering roles on the team Stronger, broader and more reliable fraud signal directly improves detection accuracy, reduces customer losses and protects brand trust Key Responsibilities Own the design, build and operation of the data lake and ingestion platform end-to-end, from architecture through production reliability Build low-latency batch and streaming pipelines that ingest signals from internal and external sources, normalize them to a common schema, enrich them with context and serve model-ready data to the layers above Make adding a new data source a routine task rather than a project, so our view of risk keeps widening over time Establish data quality, freshness, completeness, lineage and observability so the platform is trustworthy enough to automate on top of Build data pipelines that ground generative AI, including unstructured text and threat intelligence processing, embedding generation, vector storage and retrieval Own deployment, CI/CD and operational reliability of the platform on Kubernetes Partner with data science, product and architecture to turn the platform into a shared foundation across 360 Fraud Protection Required Qualifications Extensive experience building and operating large-scale data platforms and data lakes, with comfort working at high data volumes Deep, hands-on expertise with Apache Spark, Apache Flink and modern big-data systems Proven command of best practices for building and maintaining data pipelines in both batch and streaming modes Strong production engineering skills across the full delivery lifecycle, including Kubernetes and CI/CD tooling, with the ability to ship end-to-end A track record of owning data infrastructure end-to-end with limited supervision Preferred Qualifications Experience with generative AI and embedding models, including embedding pipelines, vector databases and retrieval A cybersecurity or threat intelligence background, with hands-on exposure to threat types such as phishing, mobile threats and malware Familiarity with transaction data and transaction fraud signals Compensation Base salary range: $180 - $270 Bonus / commission: 15% Travel Minimal travel expected. This is an on-site role based in New York City, with 3-4 days per week in the office AppGate is An Equal Opportunity/Affirmative Action Employer and a federal contractor subject to the Rehabilitation Act of 1973 and the Vietnam Era Veterans Readjustment Assistance Act of 1974 as amended, and their corresponding regulations. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class. Further, AppGate is an affirmative action employer committed to taking positive steps to employ, advance in employment and otherwise afford equal employment opportunity to protected veterans and individuals with disabilities. In furtherance of AppGate's policy regarding affirmative action and equal employment opportunity, AppGate has developed a written affirmative action program. This program is available for review upon request by any applicant or employee during normal business hours by contacting the company's EEO Coordinator.
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.