Jobs at TechGrove by Banyan Software (Now Hiring) — 8 open

Job Title: Senior DevOps Engineer – Modernized Application Operations & SRE

Overview

We are seeking a highly experienced and hands-on Senior DevOps Engineer to own the operational excellence of the modernized SaaS applications produced by the Banyan AI Factory. This is not a role focused on building the factory itself; instead, you will run the cloud operations and reliability of the modernized applications the factory delivers to our Operating Companies (OpCos).

You will join a team that provides 24x7 coverage with rotating on-call responsibilities, serving as Tier 1 Site Reliability Engineering (SRE) for our OpCos’ modernized SaaS platforms. Day to day, that means cloud operations, performance and availability monitoring/observability, disaster recovery, and security incident response across our two target clouds — Amazon Web Services (AWS) and Microsoft Azure. The ideal candidate pairs deep multi-cloud mastery with a strong commitment to operational excellence and a track record of keeping secure, highly available production systems running at scale.

Key Responsibilities

• 24x7 Operations & On-Call: Operate as part of a team providing round-the-clock coverage of OpCo modernized SaaS platforms, participating in a rotating on-call schedule to ensure continuous availability and rapid response.
• Tier 1 SRE & Cloud Operations: Serve as Tier 1 SRE for the modernized applications produced by the factory, managing day-to-day cloud operations across our two target clouds — AWS and Azure — to keep production systems healthy, performant, and secure.
• Performance & Availability Monitoring/Observability: Implement and maintain robust cloud-native observability tooling (monitoring, logging, tracing) to track performance and availability, proactively detect degradation, and drive down mean-time-to-detect and mean-time-to-resolve.
• Security Incident Response: Respond to security incidents and operational events affecting OpCo SaaS platforms, executing established runbooks, coordinating remediation, and leading post-incident reviews.
• Disaster Recovery & Resilience: Plan, test, and execute disaster recovery procedures that protect the availability and integrity of modernized applications, ensuring backup, failover, and restoration capabilities meet defined RTO/RPO targets.
• Infrastructure-as-Code & Automation: Use Infrastructure-as-Code (Terraform) and CI/CD pipelines (e.g., GitHub Actions, GitLab CI) to manage, deploy, and automate the operational environments of modernized applications, reducing toil and improving consistency.
• AI Agents & DevSecOps Scale: Build scale in our DevSecOps practice by designing, building, and operating AI agents that automate SRE tasks and incident response, reducing toil and accelerating detection, triage, and remediation.
• Hands-on Problem Solving: Serve as a technical escalation point for complex operational challenges, applying strong analytical skills to resolve infrastructure, network, and automation issues across distributed, multi-tenant SaaS environments while navigating technical ambiguity.
• Mentorship & Coaching: Mentor and coach junior DevOps/SRE engineers, fostering a culture of operational ownership, continuous improvement, and knowledge sharing in cloud-native and reliability best practices.

Required Qualifications & Experience

• Experience: 5–7 years of progressive experience in Software Engineering, DevOps, and/or Site Reliability Engineering, with a focus on operating production SaaS systems.
• Advanced Dual-Cloud Mastery (AWS & Azure): Deep, hands-on experience operating production workloads on both Amazon Web Services (AWS) (e.g., EC2, Lambda, EKS, S3, RDS) and Microsoft Azure (e.g., Container Apps, AKS, Container Storage). Both clouds are required targets for this role.
• Infrastructure-as-Code with Terraform (Required): Demonstrated, hands-on mastery of Infrastructure-as-Code using Terraform to provision and manage large-scale, distributed cloud environments. This is a hard requirement for the role.
• AI-Fluent Engineering (Required): Fluency with AI-assisted engineering tools such as Claude Code or similar, applied in practice to automate operations, accelerate troubleshooting, and improve runbooks, tooling, and incident response.
• Operations, Monitoring & Observability: Hands-on mastery of cloud-native monitoring, logging, and tracing tools, with a proven track record operating highly available production systems and meeting SLAs/SLOs.
• Application Performance Management (APM): Familiarity with APM tooling and practices (e.g., Datadog, New Relic, Dynatrace, or similar) to instrument, profile, and optimize application performance in production.
• Incident & Security Response: Demonstrated experience participating in on-call rotations, responding to production and security incidents, and executing disaster recovery procedures.
• DevSecOps & Automation: Deep history of hands-on work with CI/CD platforms (GitHub Actions, GitLab CI) and embedding DevSecOps practices directly into operational workflows.
• Containerization & Serverless: Deep expertise in container technologies (Docker/Kubernetes) and serverless architectures (AWS Lambda) supporting highly scalable and resilient distributed systems.
• Architectural Understanding: Solid understanding of modern architectural patterns (microservices, event-driven architecture, distributed systems) and experience operating security and observability patterns at scale.
• Hands-on Technical Depth: Proven history of making code contributions in modern technology languages (e.g., Python, TypeScript, Go, or similar) to build and maintain automation and operational tooling.
• Communication & Collaboration: Exceptional communication, presentation, and collaboration skills, with a proven ability to coordinate across OpCo and factory teams and manage expectations with both technical and business stakeholders.

Preferred Skills (A Plus)

• Experience operating on Google Cloud Platform (GCP). GCP is a nice-to-have, not a requirement — AWS and Azure are the target clouds for this role.
• Prior experience building and operating a multi-tenant SaaS (Software as a Service) solution at scale.
• Experience with advanced data infrastructure and processing pipelines for GenAI-related systems (e.g., Vector Databases, knowledge graphs).
• Direct experience training or mentoring other engineers in platform-level technologies or methodologies.
• Familiarity with advanced cloud security tools like Wiz, Prisma Cloud, and Checkov.