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AI DevOps. Engineer

Expedient

Indianapolis, INHybridJob$120–150K/yrPosted 1mo agoSeen in employer's feed 5 days ago

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At a glance

Compensation
$120–150K/yr
Location
Indianapolis, INHybrid
Work Authorization
Not specified

Requirements

Credentials this posting asks for.

Bachelor's degree

Job overview

Expedient is hiring an AI DevOps. Engineer. Expedient is seeking a senior AI DevOps Engineer to join the AI CTRL product team. This role involves building a framework for managing, configuring, and deploying agentic workflows, tooling applications, and AI integrations for clients. The engineer will own the entire path from commit to production, focusing on Git-driven CI/CD, infrastructure as code, release and config management, observability, and LLMOps practices to ensure reliable and cost-efficient model-powered systems.

Key focus areas include Design and build Git-based pipelines for automated build, test, and deploy processes, Use Terraform, Helm, and GitOps to provision and manage Kubernetes clusters and environments, and Manage environment and deployment configuration as code across client deployments.

Successful candidates bring Bachelor's In Computer Science, Bachelor's In Engineering, and Bachelor's In Information Systems. Important skills include Git-Driven CI/CD, Infrastructure as Code, Release Management, Config Management, Observability, and LLMOps Practices.

Skills & qualifications

RequiredNice to have

Skills

Git-Driven CI/CDInfrastructure as CodeRelease ManagementConfig ManagementObservabilityLLMOps PracticesAnthropic ClaudeOpenAIGoogle GeminiRAGMCP IntegrationsCI/CD PipelinesRetool AppsAgentic WorkflowsData ConnectorsTerraformHelmGitOpsArgo CDFluxKubernetesNutanix NKPConfiguration ManagementVersioningElastic/ECKMonitoringTelemetry Distributed TracingSLOs/SLIsModel/Prompt Evaluation PipelinesA/B Testing of Prompts and ModelsMulti-Provider Traffic Routing and FailoverToken/Cost DashboardsChange & Risk ManagementCompliance-as-CodeSOC 2 Audit LoggingSecrets ManagementVaults/Sealed-SecretsSSO/OIDC ConfigurationAutomation MarketplaceIaC ModulesCollaborateDocumentationGit-Based CI/CDOperating and Automating ClustersNamespacesWorkloadsContainer LifecycleOpenTelemetry TracingDefining AlertsPython

Qualifications

3-5 Years in DevOps, Platform Engineering, Site Reliability, or MLOps/LLMOps ExperienceBachelor's in Computer Science, Engineering, Information Systems, or Related Field or Equivalent Practical ExperiencePrior Managed Service Provider ExperiencePrior SaaS Company ExperiencePrior Enterprise Technology Team Experience

Benefits

Tuition Assistance
Paid Time Off
Parental Leave
Medical Insurance
Dental Insurance
Vision Insurance
401(k) Match

Full job description

Join Expedient's AI CTRL product team as our AI DevOps Engineer — a senior, hands-on engineer who will build the framework that manages, configures and ships agentic workflows, tooling applications, and AI integrations to clients quickly, safely, and repeatably. You'll own the path from commit to production: Git-driven CI/CD, infrastructure as code, release and config management, observability, and the LLMOps practices that keep model-powered systems reliable and cost-efficient. This is a build role — you won't be maintaining someone else's pipelines, you'll be creating the framework the AI Dev team builds on.

Because AI CTRL runs on enterprise model APIs (Anthropic Claude, OpenAI, Google Gemini) with RAG and MCP integrations rather than training custom models, this role is LLMOps-focused: prompts, configs, and integrations are the primary code surface, and the operational challenges are deployment velocity, traceability, cost, and risk at scale.

What You'll Do:

  • CI/CD Pipelines: Design and build Git-based pipelines that automate build → test → deploy for Retool apps, agentic workflows, MCP servers, and data connectors — turning manual client deployments into repeatable, gated releases.

  • Infrastructure as Code: Make the platform reproducible. Use Terraform, Helm, and GitOps (ArgoCD/Flux) to provision and manage Kubernetes (Nutanix NKP) clusters and per-client environments as code.

  • Configuration Management: Manage environment and deployment configuration as code across a growing fleet of client deployments — eliminate config drift and one-off manual changes.

  • Release Management: Own versioning, environment promotion, release gates, and clean rollback. Maintain versioned, deployable artifacts so any release can be reproduced or reverted.

  • Observability & Tracing: Build the monitoring backbone — Elastic/ECK, APM, and telemetry distributed tracing — with deployment health, SLOs/SLIs, and usage/cost instrumentation across all client deployments. Strengthen alerting so issues surface before clients feel them.

  • LLMOps Practices: Stand up prompt and configuration versioning, model/prompt evaluation pipelines, A/B testing of prompts and models, multi-provider traffic routing and failover, and token/cost dashboards — the AI-specific discipline that keeps model-powered systems accurate, available, and affordable.

  • Change & Risk Management (incl. Compliance): Implement controlled-change processes — approvals, audit trails, and guardrails — with compliance-as-code for SOC 2 audit logging, secrets management (e.g., vaults/sealed-secrets), and SSO/OIDC configuration.

  • Automation Marketplace: Build an internal library of vetted, reusable workflows, connectors, and IaC modules that accelerate client delivery — and graduate proven items into a client-facing catalog aligned to the Agentic Workflow Engine (AWE).

  • Collaborate & Document: Partner with the AI Dev engineering team on platform standards; write the runbooks, release guides, and architecture docs that let the framework scale beyond

What We're Looking For:

  • Experience: 3–5 years in DevOps, platform engineering, site reliability, or MLOps/LLMOps. Prior experience at a managed service provider, SaaS company, or enterprise technology team is a strong plus.

  • Git-based CI/CD: designing automated build/test/deploy pipelines from scratc

  • Infrastructure as Code: Terraform and Helm; GitOps with ArgoCD or Flu

  • Kubernetes: operating and automating clusters (Nutanix NKP or equivalent); namespaces, workloads, container lifecycle

  • Observability: Elastic/ECK, APM, OpenTelemetry tracing; defining alerts, SLOs/SLIs (Prometheus/Grafana experience transfers)

  • Scripting & data: strong Python and Bash; SQL fundamentals

  • Secrets & identity: secrets management (Vault or equivalent), SSO/OIDC configuration (Entra ID, Okta, OneLogin)

  • Workflow orchestration: Argo Workflows, Airflow, or similar (a plus)

  • LLM APIs: working familiarity with Anthropic Claude, OpenAI, and/or Google Gemini — prompt construction, tool use/function calling, token management

  • RAG & MCP awareness: chunking, embedding, vector search, context-window management; Model Context Protocol integrations (a plus)

  • Compliance exposure: SOC 2 audit logging and controls-as-code (a plus)

  • Builder mindset: sees a manual process and automates it; ships the framework, not just the fix

  • Automation-first & reliability-minded: treats infrastructure, config, and compliance as code; thinks in SLOs, blast radius, and rollback

  • Documentation instinct: writes the runbook before calling something done; updates the guide when the process changes

  • Risk-aware: balances deployment velocity with controlled change and auditability

  • Self-directed, strong ownership mentality, excellent communicator, thrives in a fast-paced environment

  • Education: Bachelor's in Computer Science, Engineering, Information Systems, or related field (or equivalent practical experience).

Location & Compensation:

Indianapolis, Cleveland, or Pittsburgh. Hybrid work model. Regional travel may be required.

Salary for this position is directly related to your own experience, knowledge, and skills.  Estimated range for this role is $120,000 to $150,000

#LI-hybrid

WORKING FOR EXPEDIENT We prioritize ongoing education and continuous innovation to remain at the forefront of the information technology landscape. Our commitment to learning is reflected in our comprehensive employee training and tuition reimbursement programs, which are driven by our employees and funded by Expedient 100%. For our full-time employees we offer an exceptional benefits package including three weeks of paid time off annually that increases with tenure plus your birthday off and a health holiday to be used for preventive care. We offer parental leave, top-tier medical, dental, and vision, disability and life insurance, at an affordable rate, wellness engagement opportunities, and a 401(k) with a generous match. We also recognize the importance of a comfortable and convenient work environment. We offer a hybrid work model for many roles, paid parking and other perks.

Expedient is an equal opportunity employer. Qualified applicants will receive fair and equitable consideration for employment without regard to their race, color, religion, national origin, gender, protected veteran status, disability, or any other characteristic protected by law.

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