Dev Ops Lead

Banyan Software provides the best permanent home for successful enterprise software companies, their employees, and customers. We are on a mission to acquire, build and grow great enterprise software businesses all over the world that have dominant positions in niche vertical markets. In recent years, Banyan was named the #1 fastest-growing private software company in the US on the Inc. 5000 and amongst the top 10 fastest-growing companies by the Deloitte Technology Fast 500. Founded in 2016 with a permanent capital base setup to preserve the legacy of founders, Banyan focuses on a buy and hold for life strategy for growing software companies that serve specialized vertical markets.

About the Role

We're looking for an experienced DevOps Engineer to help build, automate, and maintain both our SaaS cloud infrastructure and on-premises client installations. You'll work closely with development teams to implement robust CI/CD pipelines, manage Kubernetes deployments, and ensure security across our microservices architecture in multiple environments, with a focus on search, AI, and vector database technologies.

Key Responsibilities

• Design and evolve AI-augmented CI/CD pipelines that serve as reusable blueprints across rewrite projects—supporting multi-tenant SaaS deployments, agentic automation, and environment creation through code.
  
  
• Collaborate with the AI methodology team to refine automation patterns and integrate AI-driven pipeline generation, test orchestration, and telemetry collection into the rewrite process.
  
  
• Develop automated installation and update frameworks for hybrid and customer-managed environments, emphasizing repeatability and low-touch deployment.
  
  
• Manage Azure-based SaaS infrastructure, ensuring reliability, elasticity, and security across Kubernetes and containerized services.
  
  
• Deploy, scale, and optimize Elasticsearch and vector database clusters supporting GenAI workloads.
  
  
• Implement, monitor, and tune LLM and AI service deployments on Azure (OpenAI Service, Cognitive Search, model hosting).
  
  
• Design and maintain federated authentication and identity integration across microservices (Okta, OAuth2, and SSO patterns).
  
  
• Oversee PostgreSQL/MS SQL and data infrastructure, ensuring resilience, automated backup, and performance tuning for high-throughput workloads.
  
  
• Establish observability standards—metrics, traces, and logs—for AI and non-AI services; use insights to improve future rewrites.
  
  
• Embed security automation into every deployment model, enforcing Zero Trust and continuous vulnerability assessment.
  
  
• Partner with development and AI teams to industrialize deployment methodology, transforming learnings from each rewrite into platform-level automation improvements.

Required Experience:

• AI-Augmented CI/CD: Proven experience building and maintaining automated pipelines (GitHub Actions or Azure DevOps) that integrate AI-assisted code generation, testing, and deployment workflows.
  
  
• Version Control & Collaboration: Deep experience with Git-based systems (GitHub, Bitbucket) including managing multi-repo architectures and enforcing branching and governance standards.
  
  
• Kubernetes & Cloud Infrastructure: Advanced proficiency with Kubernetes and Helm; experienced in operating containerized microservices across multiple environments in Azure.
  
  
• Infrastructure as Code (IaC): Strong knowledge of Terraform or Bicep for creating repeatable, parameterized deployment templates used across multiple rewrite projects.
  
  
• Authentication & IAM: Hands-on experience implementing federated identity (Okta, Azure AD, OAuth2/OIDC) across microservices and SaaS environments.
  
  
• PostgreSQL & Data Layer Operations: Skilled in tuning, scaling, and backing up PostgreSQL; familiarity with managing schema migrations in automated CI/CD contexts.
  
  
• Vector & Search Systems: Operational experience with Elasticsearch and vector databases (e.g., Milvus, Pinecone, or Azure AI Search) to support AI-driven use cases.
  
  
• Azure AI & LLM Deployments: Experience provisioning and managing Azure OpenAI, Cognitive Search, and other AI workloads, including model deployment and scaling.
  
  
• Observability & Telemetry: Strong command of Prometheus, Grafana, and distributed tracing; ability to design observability frameworks that feed back into AI-driven optimization loops.
  
  
• Security by Design: Practical application of DevSecOps, vulnerability scanning, and Zero Trust principles; automation of compliance and secret management (Vault or Azure Key Vault).

Nice to have:

• AI Workflow Orchestration: Experience with orchestrating or monitoring AI agents within build or deployment pipelines.
  
  
• Deployment Automation: Experience designing agent-driven or customer-managed installers for on-premise or hybrid client environments.
  
  
• Multi-Cloud Fluency: Hands-on experience with AWS and GCP in addition to Azure; understanding of cross-cloud deployment abstractions.
  
  
• Containerization Expertise: Proficiency with Docker, container registries, and image lifecycle management in production contexts.
  
  
• Network & Service Mesh: Familiarity with ingress controllers, API gateways, and service mesh solutions such as Istio or Linkerd.
  
  
• Scripting & Automation: Strong automation skills in Bash, Python, or PowerShell; ability to prototype AI-driven automation extensions.
  
  
• Configuration Management: Practical experience creating and managing Helm charts, Kustomize overlays, and GitOps-style deployment repositories.
  
  
• Monitoring & Continuous Improvement: Skilled in defining metrics that inform both operational health and methodology evolution across rewrite cycles.
  
  
• Governance & Quality: Experience integrating code quality and security scanning tools (SonarQube, Trivy, Snyk) directly into the build pipeline.
  
  

What We're Looking For

• 10+ years of DevOps/SRE experience in both cloud and on-premise environments
• Demonstrated experience with microservices architecture
• Experience with Elasticsearch and modern AI infrastructure components
• Familiarity with vector databases (such as Pinecone, Milvus, or Weaviate)
• Experience deploying LLMs on Azure AI or similar platforms
• Experience automating complex installation processes
• Strong problem-solving abilities and communication skills

Diversity, Equity, Inclusion & Equal Employment Opportunity at Banyan: Banyan affirms that inequality is detrimental to our Global Teams, associates, our Operating Companies, and the communities we serve. As a collective, our goal is to impact lasting change through our actions. Together, we unite for equality and equity. Banyan is committed to equal employment opportunities regardless of any protected characteristic, including race, color, genetic information, creed, national origin, religion, sex, affectional or sexual orientation, gender identity or expression, lawful alien status, ancestry, age, marital status, or protected veteran status and will not discriminate against anyone on the basis of a disability. We support an inclusive workplace where associates excel based on personal merit, qualifications, experience, ability, and job performance.

Beware of Recruitment Scams

We have been made aware of individuals fraudulently posing as members of our Talent Acquisition team and extending fake job offers. These scams may involve requests for personal information or payment for equipment. 

Protect yourself by following these steps:

• Verify that all communications from our recruiting team come from an email address.
• Remember, employers will never request payment or banking information during the hiring process.
• If you receive a suspicious message, do not respond — instead, forward it to and/or report it to the platform where you received it.

Your safety and security are important to us. Thank you for staying vigilant.