{"id":611422,"url":"https://alion.io/job/pangram-senior-software-engineer-backend","title":"Senior Software Engineer (Backend)","company":{"id":47153,"name":"Pangram","domain":"pangram.com","url":"https://alion.io/company/pangram","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":220000,"max":340000,"currency":"USD","period":"year","gross":null,"usd_annual":340000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EC2","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Datadog","optional":false},{"name":"Django","optional":false},{"name":"Docker","optional":false},{"name":"Grafana","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false},{"name":"JavaScript","optional":true},{"name":"React.js","optional":true}],"status":"live","first_seen_at":"2026-09-10T17:11:01Z","employer_posted_date":"2026-09-10","last_verified_at":"2026-11-07T11:40:38Z","board_verified":true,"closed_at":null,"days_open":57,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":57},"description":"About Pangram Labs\nPangram Labs’ mission is to protect authenticity by building the world’s best AI detection systems. We publish research on state-of-the-art AI detection techniques and algorithms, and build products to bring our technology into people's daily lives.\nWe are looking for high agency, mission-driven, and passionate builders to join our team. All roles are in person in Brooklyn, New York.\nAbout the Role\nWe are looking for a backend-focused Senior Software Engineer to design, build, and scale the production systems that serve our core technology to a rapidly growing user base.\nYou will own the backend infrastructure that powers Pangram's AI detection platform. This is a senior, high-autonomy role: you'll make architectural decisions, solve hard scaling problems, and ensure our systems are reliable and performant as demand grows. You'll work across our Django backend and AWS infrastructure, collaborating closely with our frontend and machine learning teams.\nWhat You'll Do\nDesign and implement scalable backend services and APIs to serve AI detection capabilities at scale\n\nOwn the reliability, performance, and observability of production systems\n\nArchitect and maintain data pipelines, caching layers, and service infrastructure on AWS\n\nCollaborate with ML engineers to deploy and serve machine learning models in production\n\nIdentify and resolve bottlenecks across the stack as traffic and complexity increase\n\nEstablish and improve engineering best practices around testing, deployment, and incident response\n\nRequirements\n5+ years of professional software engineering experience, with a strong backend focus\n\nProficiency in Python and Django (or comparable Python web frameworks)\n\nDeep understanding of backend architecture patterns: RESTful API design, relational databases, message queues, caching strategies, and asynchronous task processing\n\nHands-on experience with AWS services (e.g., EC2, ECS/EKS, RDS, S3, SQS, CloudFront, Lambda)\n\nExperience designing systems for high availability, horizontal scalability, and graceful degradation\n\nStrong debugging and performance-profiling skills in production environments\n\nStrongly Preferred\nExperience with containerization (Docker) and container orchestration (Kubernetes)\n\nFamiliarity with CI/CD pipelines and infrastructure-as-code tools (Terraform, CloudFormation, or similar)\n\nExperience with monitoring and observability tooling (e.g., Datadog, Prometheus, Grafana, ELK)\n\nNice to Have\nExperience deploying and serving deep learning models in production (model serving frameworks, GPU infrastructure, batch vs. real-time inference)\n\nFamiliarity with React or frontend technologies sufficient to collaborate effectively across the 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