Software Engineer – Data, Streaming & Cloud Platforms (AWS)

About the position Make your mark at Comcast -- a Fortune 30 global media and technology company. From the connectivity and platforms we provide, to the content and experiences we create, we reach hundreds of millions of customers, viewers, and guests worldwide. Become part of our award-winning technology team that turns big ideas into cutting-edge products, platforms, and solutions that our customers love. We create space to innovate, and we recognize, reward, and invest in your ideas, while ensuring you can proudly bring your authentic self to the workplace. Join us. You’ll do the best work of your career right here at Comcast. (In most cases, Comcast prefers to have employees on-site collaborating unless the team has been designated as virtual due to the nature of their work. If a position is listed with both office locations and virtual offerings, Comcast may be willing to consider candidates who live greater than 100 miles from the office for the remote option.) Job Summary The ACE (Anti-Abuse & Compliance Engineering) team at Comcast builds and runs the systems that actively defend the company and its customers from major financial, legal, and security risk — preventing $1B+ in potential losses. We operate in the high-impact domains of fraud, abuse, compliance, and security, protecting customers from bad actors through capabilities like compromised-credential detection, automated re-secure, copyright abuse handling, and fraud mitigation. Our small, elite team (under 10 engineers) operates with a startup-style culture inside Comcast, owning two mission-critical platforms end-to-end: AIRES (Automated Incident Response and Engagement System) for large-scale automated mitigations, and MAD (Machine Intelligence, Analytics & Data Gathering) for advanced abuse detection and intelligence. This role stands out for its outsized ownership, massive scale, and direct business impact — you're building systems that protect Comcast in real time, every day.

Job Description

This position is ineligible for visa sponsorship. To be considered for this role, you must be legally authorized to work in the United States and not require sponsorship for employment now or in the future. We’re looking for a bright, high-energy engineer who gets things done and is excited by working on real-time data, detection systems, and large-scale cloud platforms. This role sits on Comcast’s ACE (Anti-Abuse & Compliance Engineering) team, where we build systems that detect and mitigate fraud, abuse, and security threats in real time—protecting both customers and the business. You’ll work primarily on MAD (Machine Intelligence, Analytics & Data Gathering), a cloud-native detection platform built on AWS that ingests massive streams of identity and activity events. This is a hands-on role for someone who enjoys owning problems end-to-end, authoring detection logic, and turning data into decisive action.

Responsibilities

• Design, build, and operate real-time abuse and fraud detection services processing high-volume event streams (e.g., login and identity activity).
• Author and evolve detection rules and signals (e.g., compromised account and suspicious activity logic) using streaming frameworks.
• Develop and maintain cloud-native services and APIs in Python and Java.
• Build and operate event-driven pipelines using AWS services such as Kinesis, Lambda, S3, and DynamoDB.
• Collaborate closely with security, compliance, and product partners to turn new threat patterns into production mitigations.
• Operate with strong ownership in a small, startup-style team, influencing architecture, tooling, and technical direction.
• Ensure systems are observable, scalable, and resilient in a production AWS environment.

Requirements

• Strong experience building production-grade systems in Python (Java experience a plus).
• Hands-on experience with AWS, especially Kinesis, Lambda, S3, DynamoDB, and IAM.
• Experience with Apache Flink, Kinesis Streams, or similar streaming rule engines.
• Background in data engineering, data analytics, or applied data science, with the ability to reason about signals, patterns, and false positives.
• Exposure to machine learning or statistical techniques used in detection, scoring, or classification.
• Ability to design and maintain RESTful APIs and backend services.
• Comfortable working in Linux-based production environments.
• Strong problem ownership, bias for action, and ability to operate independently in a small team.

Nice-to-haves

• Infrastructure-as-code experience (Terraform preferred).
• Experience with Java and contributing to JVM-based backend services.
• Experience with Apache NiFi for building, operating, and monitoring data ingestion and flow-based pipelines.
• Experience operating security-, fraud-, or abuse-related systems.
• Familiarity with observability tools (metrics, logging, alerting).

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