{"id":3104183,"url":"https://alion.io/job/abnormal-ai-software-engineer-1-data-platforms","title":"Software Engineer 1 - Data Platforms","company":{"id":20628,"name":"Abnormal AI","domain":"abnormal.ai","url":"https://alion.io/company/abnormal-ai","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":79,"open_postings":18,"ghost_share":0,"stale_share":0.833,"repost_share":0,"time_to_fill_p50_days":27,"computed_at":"2026-10-25T05:49:26Z"}},"role":"Backend","role_family":"Backend","seniority":"junior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":122400,"max":176000,"currency":"USD","period":"year","gross":null,"usd_annual":176000},"salary_estimate":null,"experience_years_min":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"DynamoDB","optional":false},{"name":"Go","optional":false},{"name":"OpenSearch","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Redis","optional":false},{"name":"RocksDB","optional":false},{"name":"Spark","optional":false},{"name":"Amazon Kinesis","optional":true},{"name":"Azure","optional":true},{"name":"Flink","optional":true},{"name":"GCP","optional":true}],"status":"live","first_seen_at":"2026-09-22T21:23:33Z","employer_posted_date":"2026-10-22","last_verified_at":"2026-10-26T02:45:48Z","board_verified":true,"closed_at":null,"days_open":33,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":33},"description":"About the Role\nEnterprises of all sizes trust Abnormal AI’s cloud products to stop cybercrime. These AI-native, data-intensive SaaS applications depend on fast, reliable, and secure access to massive datasets. That’s where the Data Platform team comes in: designing and operating scalable storage systems (PostgreSQL, OpenSearch, Redis, RocksDB, DynamoDB), batch and stream data processing (Kafka, Spark), orchestration (Airflow, DBT), and more.\nWe build and maintain the core infrastructure that powers Abnormal’s most data-heavy workloads, providing scalable, reliable, and efficient data platforms and services to all of engineering and data science. We also create tools that make this infrastructure simple to operate and integrate, enabling teams to deliver faster with confidence.\nWe’re looking for a Software Engineer I who is eager to learn and ready to take on meaningful technical challenges. You’ll work alongside experienced engineers, contribute to ambitious projects, and grow your skills while helping to scale the systems that support Abnormal’s rapid growth.\nWhat you will do \nContribute to the design, development, and operation of core components of Abnormal’s data platform.\nBuild tools and services that make it easy for other teams to adopt and scale data systems.\nHelp automate infrastructure and operations to improve reliability, performance, and scalability.\nApply cutting-edge GenAI techniques to build smarter developer and operator experiences.\nCollaborate across engineering teams to solve scalability and reliability challenges.\nTake ownership of projects, delivering features end-to-end with guidance from senior engineers.\nWhat you bring\n1+ years of professional experience in software engineering: backend, distributed systems, or infrastructure preferred.\nSolid programming skills in Python, Go, or a similar language (school, personal, or work experience all count).\nStrong software engineering fundamentals like data structures, clean code, testing, and debugging.\nInterest in learning about AWS, Databricks, and technologies in our stack (databases, streaming, orchestration).\nCuriosity, problem-solving skills, and a willingness to ask questions.\nAbility to work both independently and as part of a team, and strong communication skills.\nNice to Have (but you can also learn here)\nExperience with one or more of: Kafka, Kinesis, Flink.\nFamiliarity with cloud platforms (AWS, GCP, Azure).\nExposure to large-scale or data-intensive systems.\nWhy you’ll love it here\nYou’ll be part of a high-impact team solving problems that matter.\nYou’ll learn from and work with experienced engineers in a collaborative, supportive environment.\nYou’ll get real opportunities for ownership and career growth early in your journey.\nYou’ll help shape the future of our data platform at a fast-growing, AI-first company.\nActual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location.\nIn addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package.\nBase salary range:\n$122,400—$176,000 USD\nA note on AI in our process: \n Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards.\nAbnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. 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