Senior Software Engineer - Authentication

About the role

Pindrop is the Real Human + Right Human® Identity Trust Platform for the AI era. As AI-driven fraud and deepfakes erode trust in digital communication, Pindrop delivers continuous identity verification and deepfake detection across voice, video, and digital interactions in real time. Enterprises rely on Pindrop to secure billions of high-risk customer interactions each year, including top U.S. banks, as well as leading insurers and healthcare providers. Powered by models trained on more than 1.5 billion real-world interactions annually and protected by 300+ patents, Pindrop restores trust while reducing fraud, lowering operational costs, and improving customer experience. Recognized by TIME as one of the Top 10 Most Influential Software Companies of 2026 and by Inc. for Best in Business for Innovation, Pindrop is backed by leading investors including Andreessen Horowitz, IVP, and CapitalG.

Responsibilities

• Design, develop, test, deploy, and monitor high-performance backend services and APIs using Go and Python, with an emphasis on secure, low-latency authentication and identity workflows.
• Build and maintain cloud‑native services across AWS and GCP (e.g., S3, DynamoDB, Kinesis, IAM) with a focus on reliability, scale, and secure production operation, including data pipelines that feed downstream ML and risk models used in authentication decisions.
• Deliver features and enhancements through the full software development lifecycle, including implementation, automated testing, deployment, and operational support, using CI/CD and infrastructure‑as‑code practices.
• Tackle complex software engineering problems in authentication, identity, and fraud prevention-contributing to architecture decisions, threat‑aware design, and continuous improvement of engineering best practices across the team.
• Integrate and consume AI/ML capabilities (for example, model-backed risk scores, deepfake detection signals, or ML‑driven policies) by collaborating with Research, MLOps, and Protect/Passport teams, and help productionize these models into scalable, observable services.
• Use observability and diagnostics tooling (metrics, logging, tracing, dashboards) to troubleshoot production issues, reduce alert noise, and systematically improve reliability and latency for authentication journeys.
• Partner closely with software engineering, test engineering, research, product, Protect, Passport, and Core teams to deliver new capabilities and improve existing ones, including AI‑enhanced identity and fraud experiences for customers.
• Participate in the team's on‑call rotation, including helping cover after‑hours alerts as we expand distributed support coverage for our customer‑facing authentication platform.
• Contribute to documentation, runbooks, and design reviews that clarify how authentication services behave, how AI/ML components are used safely, and how other engineers should integrate with the platform.

Requirements

• You are a strong communicator who collaborates effectively across engineering, product, test, research, and other cross‑functional partners.
• You are an owner who can independently drive work from design through production with strong judgment around performance, scale, security, and reliability in authentication flows.
• You are energized by solving hard technical problems and improving systems, processes, and engineering standards, especially in high‑stakes, security‑sensitive environments.
• You are resilient, adaptable, and effective in environments that require context switching, rapid troubleshooting, and operating through ambiguity while maintaining high quality.
• You are resourceful and curious-comfortable learning new tools (including AI tooling) and teaching yourself what you need to move a problem forward, then sharing that knowledge with the team.
• You are invested in helping others grow and bring a mentorship mindset to code reviews, pairing, and day‑to‑day collaboration.
• Your skill-set
• 5-7+ years of professional software development experience building backend services and APIs.
• Strong experience with Go, Python, or similar languages, plus a solid foundation in data structures, algorithms, concurrency, and Linux-based development.
• Hands-on experience designing and operating cloud-native systems in AWS or GCP, including managed services such as S3, DynamoDB, Kinesis, and IAM.
• Experience with CI/CD, DevOps, Docker, Kubernetes, and production ownership, including deploying, monitoring, troubleshooting, and supporting services in li

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