Site Reliability Engineer

Prediktive; New York (NY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Prediktive is seeking an experienced Site Reliability Engineer based in the United States to help build and operate bank-grade AI infrastructure. You will own reliability initiatives across stateful AI systems, model serving, and data pipelines while partnering with cross-functional teams to ensure scalable, secure production systems.

You will design and maintain monitoring, runbooks, and incident response processes, mentor engineers, and push for proactive reliability and security practices in

Qualifications

• 5+ years in SRE or similar roles supporting production environments.
• Experience mentoring and guiding other engineers.
• Strong understanding of CI/CD, Kubernetes and containerization, networking, databases, and cloud security.

Responsibilities

• Define and drive reliability initiatives (SLOs, capacity planning, resilience).
• Design, build, and run monitoring, alerting, and infrastructure.
• Participate in incident management and perform root cause analyses.
• Identify and fix misconfigurations and architectural risks.
• Automate operational work and build capacity planning tools.
• Own capacity and recovery for stateful AI infrastructure.
• Set best practices for security, compliance, and reliability.

Skills

SRE experience

CI/CD

Kubernetes

Networking

Databases

Cloud security

Observability

Incident response

Python

Go

Bash

Learning mindset

Education

Bachelor's degree in Computer Science / Systems Engineering or related field

Tools

Terraform

Pulumi

Grafana

Datadog

Sentry

PagerDuty

incident.io

Job description

We are looking for a Site Reliability Engineer based in the US to work on a long-term project for one of our clients, a Software Development company based in New York.Our client is building a secure, bank-grade AI infrastructure and developing cutting-edge applications designed to power the next generation of modern banking and financial services.The person in this role will keep our client's banking AI platform reliable, scalable, and fast as they grow from a handful of live banks to hundreds.

Responsibilities

• Define and drive reliability initiatives: SLOs, capacity planning, and resilience improvements, with alerts that tell us a bank's users are affected before the bank does.
• Design, build, and run monitoring, alerting, and infrastructure.
• Participate in incident management: carry the pager, command serious incidents, run root cause analyses, and turn postmortems into lasting fixes.
• Find and fix misconfigurations and architectural risks before they turn into incidents.
• Automate operational work, building tools for capacity planning, graceful rollouts, and safe data access so reliability never depends on manual steps.
• Own capacity and recovery for our stateful and AI infrastructure: databases, model serving, and job pipelines.
• Set best practices for security, compliance, and reliability, and work across teams to build them into every stage of how we ship.

Requirements

• Advanced Level of English.
• 5+ years in SRE or similar roles supporting production, with a record of mentoring and guiding other engineers.
• Broad knowledge of CI/CD, Kubernetes and containerization, networking, databases, and cloud security, with a strong understanding of failure modes and troubleshooting across all layers of the stack.
• Expertise in infrastructure as code: Terraform, Pulumi, or similar.
• Deep familiarity with observability and incident response: Grafana, Datadog, Sentry, PagerDuty, incident.io, or similar.
• Proficiency in at least one major cloud: Azure, AWS, or GCP.
• Strong programming skills in Python, Go, Bash, or similar.
• Hands-on experience operating stateful distributed databases in production environments, including memory management, replication, backups, and recovery procedures.
• Proven ability to diagnose complex technical issues, identify root causes, and implement robust, long-term solutions rather than temporary workarounds.
• Strong learning mindset and a proactive, hands-on approach to engineering, with the ability to quickly learn new systems, build scalable solutions, and continuously improve system reliability and maintainability.
• Strong problem-solving, meticulous attention to detail, and a real commitment to operational excellence.

Bonus Points

• Bachelor’s Degree in Computer Science, Systems Engineering or related fields.
• Experience with graph databases, GPU or LLM serving, or workflow engines in production environments.
• Experience with Microsoft Azure cloud services.
• Experience working with regulated customers and compliance-sensitive environments.
• Experience designing, deploying, or maintaining single-tenant and customer-hosted solutions.