Software Engineer

Who We Are

Pindrop is a cybersecurity company delivering continuous identity verification across voice, video, and digital interactions. Powered by the Pindrop Intelligence Network, our unified trust platform helps enterprises answer three critical questions:

Is this identity synthetic? Detect AI-generated and manipulated voice and video.
Is this identity risky? Identify fraud, suspicious behavior, and other risk signals.
Is this identity known? Authenticate identities using voice, device, behavioral, and other signals.

Pindrop brings this intelligence together across purpose-built trust engines to help organizations make informed decisions in real time — protecting customers, workforce interactions, and emerging AI-driven interactions.

Pindrop protects billions of high-risk interactions for enterprises, including leading financial institutions, insurers, and healthcare organizations. Its technology is informed by more than 8 billion real-world interactions annually and protected by 300+ patents.

Recognized by TIME as one of the 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.

What you'll do

As a Senior Software Engineer on the Authentication team, you will help build and scale the cloud services behind Passport as the team continues moving customers onto its cloud platform. You’ll focus on highly reliable, secure authentication services that power voice-based identity verification at scale, while increasingly leveraging AI/ML-driven signals and tooling to strengthen fraud defenses and engineering productivity. More specifically, you will:

• 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.