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Prodigal is building AI agents for loan servicing and collections, processing sensitive borrower conversations and financial data at scale. Founded in 2018 by IITB alumni, the company has 100+ enterprise customers across North America and backing from Y Combinator, Accel, and Menlo Ventures.
As a DevSecOps Engineer, you'll work alongside the DevSecOps Lead to embed security across cloud infrastructure, CI/CD pipelines, Kubernetes workloads, and AI systems. This role uniquely combines security ownership with AI/ML infrastructure exposure, including real-time voice AI infrastructure at production scale with sub-1 second latency requirements.
Key responsibilities include:
- AWS infrastructure management and optimization (EC2, VPC, IAM, S3, CloudWatch) using Terraform for infrastructure-as-code
- Cloud cost management and optimization, identifying rightsizing opportunities and eliminating waste
- Kubernetes cluster operations and troubleshooting, including pod scheduling, resource limits, autoscaling (Karpenter), and service mesh (Istio)
- Monitoring and incident response using Prometheus and Grafana, including root cause analysis and runbook development
- CI/CD pipeline architecture with integrated security guardrails (SAST, dependency scanning, secrets detection) using TrueFoundry
- AI/ML infrastructure support including Databricks environment management, GPU workload scheduling, and model deployment pipelines
- Automation of repetitive operational tasks using Python and Bash
You'll need 3-5 years of hands-on DevOps/DevSecOps experience in product companies or startups, with strong AWS proficiency and production Kubernetes experience. Required skills include CI/CD pipeline expertise (GitHub Actions, GitLab CI, ArgoCD), infrastructure-as-code (Terraform/CloudFormation), scripting (Python/Bash), monitoring tools (Prometheus/Grafana), and security fundamentals (IAM, secrets management, SOC2/PCI-DSS). Project ownership and clear communication are essential in this small team environment. Bonus experience includes ML/ML infrastructure, GPU instances, and model serving frameworks.
