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Ai Integration Engineer Jobs in Indiana (NOW HIRING)

AI | Carmel, IN (Hybrid) | Full-Time About Bioscope.AI Bioscope.AI is an early-stage precision ... Every integration you ship directly expands what our platform can do and how many practices we can ...

AI Engineer

Indianapolis, IN · On-site

$100 - $130/hr

Integrate AI systems with existing IT infrastructure and ensure seamless operation. Ensure AI ... Engineering, Operations, support functions, and other IT professionals. * Design, develop, and ...

Integrate AI systems with existing IT infrastructure and ensure seamless operation. Ensure AI ... Engineering, Operations, support functions, and other IT professionals. * Design, develop, and ...

... engineer. This role requires a well-rounded full-stack background across modern web technologies ... Integration with LLMs and AI APIs (e.g., Azure OpenAI, AWS Bedrock, or similar platforms)

... engineer. This role requires a well-rounded full-stack background across modern web technologies ... Integration with LLMs and AI APIs (e.g., Azure OpenAI, AWS Bedrock, or similar platforms)

Web application developer

Crane, IN · On-site

$120 - $170/hr

AI/ML Integration & Intelligent Solutions * Design and implement AI-enabled application features, such as: * Integration with LLMs and AI APIs (e.g., Azure OpenAI, AWS Bedrock, or similar platforms)

... engineer. This role requires a well-rounded full-stack background across modern web technologies ... Integration with LLMs and AI APIs (e.g., Azure OpenAI, AWS Bedrock, or similar platforms)

AI/ML Integration & Intelligent Solutions * Design and implement AI-enabled application features, such as: * Integration with LLMs and AI APIs (e.g., Azure OpenAI, AWS Bedrock, or similar platforms)

Showing results 21-40

Ai Integration Engineer information

See Indiana salary details

$42.3K

$118.3K

$165.1K

How much do ai integration engineer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for ai integration engineer in Indiana is $118,256.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,000.00 and $133,200.00 per year, depending on experience, location, and employer.

What is an AI integration engineer?

AI Integration Engineers are professionals who specialize in implementing artificial intelligence solutions into existing systems, products, or workflows. They work closely with data scientists, software developers, and business teams to ensure that AI models and technologies are effectively deployed and seamlessly integrated. Their responsibilities often include customizing AI tools, developing APIs, ensuring data compatibility, and monitoring performance post-integration. These engineers play a crucial role in bridging the gap between AI research and practical business applications.

What are some common challenges faced by AI integration engineers when deploying machine learning models into existing business systems?

AI Integration Engineers often encounter challenges such as ensuring compatibility between machine learning models and legacy systems, managing data privacy and security, and optimizing model performance for real-time applications. They must also address issues related to model scalability and monitoring, as well as facilitate smooth collaboration between data science, IT, and business teams. Overcoming these challenges requires strong problem-solving skills, effective communication, and a deep understanding of both AI technologies and enterprise infrastructure.

What are the key skills and qualifications needed to thrive as an AI integration engineer, and why are they important?

To thrive as an AI Integration Engineer, you need a solid background in computer science, programming (Python, Java, or similar), and experience with AI/ML frameworks, often supported by a bachelor's degree in a related field. Familiarity with cloud platforms (such as AWS, Azure, or Google Cloud), API development, and tools like TensorFlow or PyTorch is typically required. Strong problem-solving abilities, collaboration, and clear communication are essential soft skills for bridging technical and business needs. These competencies ensure successful deployment and seamless integration of AI solutions into existing systems, driving innovation and business value.

What is the difference between Ai Integration Engineer vs Data Scientist?

AspectAi Integration EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; certifications in AI/ML toolsBachelor's or higher in CS, Statistics, or related; advanced degrees common
Work EnvironmentDeveloping and deploying AI solutions, integrating AI APIs into applicationsAnalyzing data, building predictive models, interpreting complex datasets
Employer & Industry UsageTech companies, AI service providers, software firmsResearch institutions, tech companies, finance, healthcare

While both roles involve AI, the Ai Integration Engineer focuses on implementing and integrating AI solutions into applications, whereas the Data Scientist analyzes data to develop models and insights. The roles often overlap but differ mainly in their primary focus: deployment versus analysis.

Are AI Integration Engineers highly paid?

AI Integration Engineers typically earn higher-than-average salaries due to their specialized skills in AI systems, programming, and data analysis. Compensation varies based on experience, location, and industry, but they are generally well-compensated compared to many other engineering roles.

What are popular job titles related to Ai Integration Engineer jobs in Indiana?

For Ai Integration Engineer jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Ai Integration Engineer jobs in Indiana look for?

The top searched job categories for Ai Integration Engineer jobs in Indiana are:

What cities in Indiana are hiring for Ai Integration Engineer jobs?

Cities in Indiana with the most Ai Integration Engineer job openings:

Infographic showing various Ai Integration Engineer job openings in Indiana as of August 2026, with employment types broken down into 75% Full Time, 20% Part Time, and 5% Contract. Highlights an 65% Physical, 5% Hybrid, and 30% Remote job distribution, with an average salary of $118,256 per year, or $56.9 per hour.

AI DevOps. Engineer

Expedient Holdings USA, LLC

Indianapolis, IN • On-site

$120 - $150/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago


Key responsibilities

  • Design and build Git-based CI/CD pipelines to automate build, test, and deployment processes.

  • Manage infrastructure as code using Terraform, Helm, and GitOps tools to provision and operate Kubernetes clusters and client environments.

  • Develop and maintain observability and monitoring systems, including alerting, telemetry, and performance tracking across client deployments.


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.

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 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 scratch.
  • Infrastructure as Code: Terraform and Helm; GitOps with ArgoCD or Flux.
  • 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.

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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