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Ai Integration Jobs (NOW HIRING)

Lightedge

Sr. AI Integration Engineer

Kansas City, MO · On-site

$101K - $136K/yr

The Senior AI Integration Engineer plays a central role in building, integrating, deploying, and supporting AI-driven workflows across Lightedge's core operational and business systems. This position ...

Lightedge

Sr. AI Integration Engineer

Lenexa, KS · On-site

$97K - $131K/yr

The Senior AI Integration Engineer plays a central role in building, integrating, deploying, and supporting AI-driven workflows across Lightedge's core operational and business systems. This position ...

Virtusa

AI Integration - Backend Services

San Jose, CA · On-site

As a Senior Software Engineer specializing in AI Integration with Backend Services, you will play a pivotal role in designing, developing, and deploying robust and scalable backend systems that ...

Virtusa

AI Integration - Backend Services

San Jose, CA · On-site

As a Senior Software Engineer specializing in AI Integration with Backend Services, you will play a pivotal role in designing, developing, and deploying robust and scalable backend systems that ...

Bcbsri

Senior AI Integration Engineer

Providence, RI · On-site +1

$151K - $243K/yr

Focus on integrating diverse data sources, refining AI interactions through prompt engineering, and collaborating with cross-functional teams to drive artificial intelligence adoption and innovation.

KDA Consulting Inc

Lead AI Integration Engineer

Herndon, VA · On-site

$105K - $138K/yr

Led AI engineering integration efforts for Enterprise Mind, partnering closely with Sponsor stakeholders, AWS teams, and cross-functional engineering groups to design, integrate, and operationalize ...

KDA Consulting Inc

Lead AI Integration Engineer

Herndon, VA · On-site

$105K - $138K/yr

Led AI engineering integration efforts for Enterprise Mind, partnering closely with Sponsor stakeholders, AWS teams, and cross-functional engineering groups to design, integrate, and operationalize ...

Lightedge

Sr. AI Integration Engineer

Des Moines, IA · Hybrid

Our owned and operated facilities, integrated DR solutions, and premium compliant cloud choices ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

Lightedge

Sr. AI Integration Engineer

Dallas, TX · Hybrid

Our owned and operated facilities, integrated DR solutions, and premium compliant cloud choices ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

Lightedge

Sr. AI Integration Engineer

Lewisville, TX · Hybrid

Our owned and operated facilities, integrated DR solutions, and premium compliant cloud choices ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

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Ai Integration information

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How much do ai integration jobs pay per year?

As of Jul 7, 2026, the average yearly pay for ai integration in the United States is $117,986.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,000.00 and $146,500.00 per year, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as AI research director, senior machine learning engineer, or AI solutions architect, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership, strategic planning, and expertise in tools like TensorFlow or PyTorch, with compensation reflecting experience and impact on business or technology development.

What are some common challenges faced when integrating AI solutions into existing business processes?

One of the most common challenges in AI integration is ensuring that new AI tools seamlessly interact with legacy systems and data formats. Team members often need to address data quality issues, adapt workflows, and manage stakeholder expectations regarding the capabilities and limitations of AI. Collaboration with IT, operations, and business units is essential to customize solutions and ensure user adoption. Additionally, ongoing monitoring and retraining of AI models is necessary to maintain performance and align with evolving business goals.

What is an AI integration job?

An AI integration job involves implementing artificial intelligence systems into existing software or workflows to improve functionality or automate processes. It requires skills in programming, data analysis, and understanding AI tools and platforms. Professionals in this role often collaborate with development teams and may need knowledge of machine learning, APIs, and cloud services.

How much does an AI integration specialist make?

An AI integration specialist typically earns between $70,000 and $130,000 annually, depending on experience, location, and industry. Professionals with skills in machine learning, programming, and cloud platforms tend to have higher salaries, especially in tech-focused environments.

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

To excel as an AI Integration Specialist, you need a solid background in computer science, proficiency in programming languages (such as Python), and experience with machine learning frameworks, often supported by a relevant degree or certifications. Familiarity with cloud platforms (like AWS, Azure, or Google Cloud), APIs, and integration tools is typically required. Strong problem-solving skills, effective communication, and the ability to collaborate across teams make someone stand out in this role. These competencies are crucial for successfully implementing AI solutions that align with business needs and ensuring seamless system interoperability.

What is AI integration?

AI integration refers to the process of incorporating artificial intelligence technologies into existing systems, applications, or business processes to enhance automation, improve decision-making, and optimize performance. This can involve connecting AI models, such as machine learning algorithms or natural language processing tools, with software platforms, databases, or workflows. The goal is to enable systems to analyze data, learn from patterns, and perform tasks that traditionally required human intelligence. AI integration can benefit a wide range of industries, including healthcare, finance, manufacturing, and customer service.

What is the difference between Ai Integration vs Data Analyst?

AspectAi IntegrationData Analyst
Required CredentialsBachelor's in Computer Science, Engineering, or related fields; knowledge of AI/ML toolsBachelor's in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentTech companies, AI development teams, software firmsBusiness, finance, healthcare, and other industries analyzing data
Employer & Industry UsageDeveloping AI solutions, integrating AI into productsInterpreting data, generating reports, supporting decision-making

While Ai Integration specialists focus on implementing AI systems and integrating AI technologies into applications, Data Analysts interpret data to provide insights and support business decisions. Both roles require analytical skills, but Ai Integration emphasizes technical development and system integration, whereas Data Analysts focus on data interpretation and reporting.

How to become an AI integration specialist with no experience?

To become an AI integration specialist with no experience, start by learning foundational skills in programming languages like Python and understanding AI concepts such as machine learning and APIs. Gaining hands-on experience through online courses, tutorials, and small projects helps build practical skills, while certifications in AI or cloud platforms can enhance your credentials. Entry-level roles may require demonstrating problem-solving abilities and familiarity with AI tools and frameworks.
More about Ai Integration jobs
What cities are hiring for Ai Integration jobs? Cities with the most Ai Integration job openings:
What states have the most Ai Integration jobs? States with the most job openings for Ai Integration jobs include:
What job categories do people searching Ai Integration jobs look for? The top searched job categories for Ai Integration jobs are:
Ai Integration jobs near you
Infographic showing various Ai Integration job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $117,986 per year, or $56.7 per hour.
Sr. AI Integration Engineer

Sr. AI Integration Engineer

Lightedge

Kansas City, MO • On-site

$101K - $136K/yr

Other

Re-posted 12 days ago

Job description

LightEdge Solutions is developing the IT solutions that will propel businesses forward over the next 10 years. Using a combination of shared and private/dedicated platforms, LightEdge has been successful in offering businesses alternatives that streamline operations, improve reliability and reduce costs.
If you are passionate about creating real solutions that help businesses with cutting-edge technology, want to be challenged to think out of the box and be in a position where you can impact change on a daily basis, then LightEdge can offer you a dynamic corporate environment built on teamwork and personal responsibility.

The Senior AI Integration Engineer plays a central role in building, integrating, deploying, and supporting AI-driven workflows across Lightedge's core operational and business systems. This position is an execution partner to AI architecture leadership, helping translate agentic design concepts and approved business needs into production-ready AI agents, automations, and integrations that improve workflow execution, operational efficiency, and decision support.

The ideal candidate combines strong software engineering and systems integration skills with practical experience delivering AI-enabled workflows in business environments. This person must be comfortable working directly with stakeholders to gather requirements, refine scope, and iterate quickly, while also owning a backlog of business-facing AI workflows and serving as the primary technical owner for those workflows once they move into production.

Key Responsibilities
  • AI Agent, Harness & Workflow Development: Design, develop, and maintain production-grade AI agents, harnesses, workflows, services, and integrations that support internal business processes and cross-functional execution.
  • AI Agent & Workflow Lifecycle Management: Own the end-to-end lifecycle of AI agents and AI-driven workflows, from intake and requirements shaping through production readiness, deployment, monitoring, support, periodic review, and continuous improvement.
  • Stakeholder Partnership: Work directly with internal teams to gather requirements, refine scope, collect feedback, and translate business needs into practical AI-enabled workflow solutions.
  • Owned Backlog: Maintain and execute a backlog of high-value business-facing AI workflows and automations that align with Lightedge priorities across operations, support, sales, and other internal functions.
  • System Integration: Build and support integrations across enterprise systems such as ServiceNow, Salesforce, portals, APIs, middleware, and other workflow platforms used by the business.
  • Production Ownership: Serve as the primary technical owner for AI workflows once they move from prototype into production, unless and until a deliberate transition to another long-term owner is defined.
  • Operational Support: Provide first-level support for production AI workflows that support critical business processes, including monitoring, issue triage, defect resolution, incident coordination, and early-life stabilization.
  • Controls and Readiness: Implement the controls required for safe production adoption, including testing, evaluation, observability, secrets handling, approval steps, rollback planning, and change-management alignment.
  • Engineering Standards: Contribute to codebases, deployment pipelines, support practices, and implementation standards for AI-enabled workflow delivery.
  • Optimization: Monitor, evaluate, and optimize the accuracy, reliability, cost, and business effectiveness of deployed AI workflows and integrations.
  • Documentation: Maintain clear technical documentation, workflow diagrams, runbooks, support notes, and production-readiness artifacts for delivered solutions.
  • Cross-Functional Collaboration: Partner with AI architecture, Security, Compliance, IT, Operations, and platform teams to ensure AI workflows are secure, supportable, and aligned with governance requirements.
  • Communications: Regularly communicate delivery status, risks, support needs, and business impact to stakeholders and leadership.
  • Architecture Contribution: Contribute implementation insight and field feedback into broader AI design and governance decisions, while not serving as the primary owner of enterprise AI strategy or architecture.
Required Qualifications
  • Experience building and supporting production workflow integrations across enterprise systems such as ServiceNow, Salesforce, APIs, middleware, and related business platforms.
  • Experience taking prototypes, proofs of concept, or citizen-developed automations into governed production environments with appropriate controls, reliability, and supportability.
  • Experience supporting production applications, integrations, or automations with direct operational ownership responsibilities.
  • Working knowledge of security, access controls, logging, monitoring, and change-management practices for business-critical systems.
  • Strong proficiency in Python for AI integrations, workflow automation, and data processing.
  • Experience with one or more of JavaScript/TypeScript, Java, or C# for API and application development.
  • Experience building and supporting APIs, microservices, distributed systems, and CI/CD pipelines.
  • Experience translating business requirements into production-ready technical workflows and integrations.
  • Experience evaluating AI outputs, prompt behavior, workflow quality, and operational reliability before production release.
  • Experience deploying and supporting production systems in cloud environments such as AWS, Azure, or GCP.
  • Ability to work directly with stakeholders to gather requirements, define scope, and iterate based on feedback.
  • Excellent communication skills and ability to translate technical decisions into business impact.
  • Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
  • 5+ years of relevant experience in software engineering, systems integration, workflow automation, or AI-enabled application delivery.
Preferred Qualifications
  • Experience integrating AI-enabled workflows into ServiceNow, Salesforce, or similar enterprise platforms.
  • Experience building LLM-based applications, agents, or workflow automations using frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent tools.
  • Experience developing AI-powered assistants, copilots, or intelligent automation workflows used by business teams.
  • Experience with prompt engineering, evaluation, and tuning of generative AI systems in production contexts.
  • Experience with Kubernetes and container-based deployment models.
  • Experience with MCP-style integration patterns, orchestration layers, or agent-accessible tool frameworks.
  • Experience with SQL and working with operational or analytics data across enterprise platforms.
  • Familiarity with vector databases, RAG pipelines, and workflow patterns that combine structured system context with LLM reasoning.
  • Familiarity with observability, support runbooks, and incident response practices for automation or integration services.
  • Experience with enterprise LLM platforms including ChatGPT, Claude, Gemini, Copilot, or similar tools.
  • Previous experience owning a backlog of automation or AI workflow enhancements for internal business users.
Success Metrics
  • Timely delivery of production-ready AI workflows that move approved use cases from prototype into governed production.
  • Reduction in manual work, cycle time, or support effort through well-integrated AI automations.
  • Reliable operation and first-level support of AI workflows that support critical business processes.
  • Strong stakeholder adoption and satisfaction across the internal teams using delivered AI workflows.
  • Clear business ROI from deployed AI workflows and automations.
  • Growth of a prioritized backlog of business-facing AI workflows aligned to Lightedge objectives.
With over 20 years in business, LightEdge offers a full stack of best-in-class IT services delivering flexibility, security, and control. Our solutions include premier colocation across seven purpose-built data centers spanning Des Moines, IA, Kansas City, MO, Omaha, NE, Austin, TX, and Raleigh, NC, industry-leading private Infrastructure as a Service (IaaS) and cloud platforms, and the top global security and compliance measures. Our owned and operated facilities, integrated DR solutions, and premium compliant cloud choices make up a true Hybrid Cloud Solution Center. LightEdge annually undergoes third-party audits for ISO 20000-1, ISO 27001, HIPAA, PCI-DSS 3.2, and SSAE 18 SOC 1 Type II, SOC 2 Type II and SOC 3.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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