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Ai Integration Jobs (NOW HIRING)

Responsibilities Peraton Labs is seeking a Senior AI Integration Developer to lead the design and implementation of an AI assistant capability within an existing web application in support of RF ...

Responsibilities Peraton Labs is seeking a Senior AI Integration Developer to lead the design and implementation of an AI assistant capability within an existing web application in support of RF ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

$81 - $127/hr

As our AI portfolio continues to grow, we are looking for an AI Integration Engineer who enjoys transforming AI innovations into reliable, production-ready software. You will work hands-on with AI ...

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 ...

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 ...

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 ...

Xometry is seeking a talented Mechanical Engineer to join our Generative AI and Geometric Integration team. In this role, you will apply your foundational knowledge of mechanical design ...

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Ai Integration information

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How much do ai integration jobs pay per year?

As of Aug 21, 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 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 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 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 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 get into AI integration?

To pursue a career in AI integration, develop skills in programming languages like Python, understand machine learning frameworks, and gain experience with AI tools and APIs. Earning relevant certifications and working on projects that demonstrate AI implementation can improve job prospects.
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What states have the most Ai Integration jobs?

States with the most job openings for Ai Integration jobs include:

Infographic showing various Ai Integration job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $117,986 per year, or $56.7 per hour.

Senior AI Integration Developer

Peraton

Red Bank, NJ • On-site

Full-time

Posted 11 days ago


Peraton rating

8.3

Company rating: 8.3 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

51st of 224 rated it services


Job description

Responsibilities

Peraton Labs is seeking a Senior AI Integration Developer to lead the design and implementation of an AI assistant capability within an existing web application in support of RF spectrum monitoring for the Department of Defense. This is a technically demanding role at the intersection of applied AI, software engineering, and operational tooling.

The core focus of this position is the development of a context-aware AI assistant and the Model Context Protocol (MCP) server and tooling infrastructure that connects it to the application's data, workflows, and services. Given the sensitive nature of the operational environment, the primary deployment target is locally-hosted models (e.g., Ollama) running in air-gapped or connectivity-constrained environments - with cloud-based LLM APIs as a secondary consideration. The right candidate understands not just how to wire up a model, but how to design tool interfaces and select or tune models that perform reliably under these constraints. It is particularly important for the candidate to take the time to properly understand the application domain and CONOPs in order to develop appropriate MCP tool chains.

This individual will work closely with the broader engineering team and domain stakeholders to identify high-value AI use cases, implement and iterate on MCP tools, and evaluate and improve the quality of AI-generated outputs over time. Familiarity with the full stack is also expected, as effective AI integration requires understanding the existing system that the assistant will interact with. The core web application for this effort uses the following technologies in the stack: FastAPI backend, React frontend, and PostgreSQL database).

Key responsibilities may include: 

  • Design and implement MCP server and tool interfaces that expose application data and functionality to the AI assistant
  • Deploy and configure locally-hosted models (e.g., Ollama) for use in air-gapped or connectivity-constrained environments
  • Evaluate and select local models appropriate for specific assistant tasks; assess capability and performance tradeoffs across model sizes and families
  • Integrate LLM inference endpoints into the application backend and frontend, supporting both local and cloud-hosted models where applicable
  • Develop and refine system prompts, tool definitions, and context management strategies optimized for the capabilities and limitations of local models
  • Define and execute evaluation frameworks to assess AI output quality, tool call accuracy, and assistant reliability
  • Identify high-value use cases in collaboration with domain experts and stakeholders; translate them into concrete AI tool designs
  • Maintain and extend backend Python and TypeScript/Node.js services supporting AI functionality or work closely with other engineers to do so
  • Document AI architecture, tool schemas, prompt strategies, model configurations, and evaluation results
  • Stay current with the evolving local model and MCP ecosystem landscape
Qualifications

Required Qualifications:

  • Minimum of 8 years of experience with a Bachelor's degree; 6 years with a Master's degree; or 3+ years with a PhD in Computer Science, Computer Engineering, Information Systems, or similar/related programs.
  • Experience deploying and working with locally-hosted models (e.g., Ollama, llama.cpp, or similar) in offline or restricted network environments
  • Strong understanding of the Model Context Protocol (MCP) - server design, tool schemas, and client-server communication
  • Experience with prompt engineering and system prompt design, particularly tuning prompts for the capabilities of smaller or quantized local models
  • Experience with agentic AI patterns - multi-step reasoning, tool chaining, and error recovery
  • Familiarity with model selection tradeoffs - capability, context length, quantization, and hardware requirements
  • Ability to design structured evaluation approaches for AI output quality and tool performance
  • Strong judgment about AI assistant UX - what makes a tool call well-designed, when an AI response is actually useful, etc.
  • Proficiency in Python; familiarity with FastAPI or comparable frameworks
  • Experience with Docker and containerized service development
  • Familiarity with TypeScript/Node.js for server-side development
  • Experience with React for implementing AI assistant or chat UI components
  • Experience with Git, CI/CD pipelines, and automated testing infrastructure
  • Clear communicator across technical and non-technical audiences
  • Must be a U.S. Citizen with ability to obtain/maintain a Secret clearance
  • Candidate should be local and able to work within our Red Bank, NJ; Basking Ridge, NJ; or Silver Spring, MD locations

Desired Qualifications:

  • Experience with LangChain, LangGraph, and FastMCP
  • Experience with GPU hardware performance benchmarking on constrained edge-deployed infrastructure
  • Familiarity with performance evaluation including: tool selection accuracy, parameter extraction correctness, multi-step reasoning success rates, response quality scoring, latency benchmarking, and regression testing across model versions
  • Experience fine-tuning or adapting open-weight models for domain-specific tasks
  • Familiarity with RAG (retrieval-augmented generation) architectures and vector databases in offline or on-premise deployments
  • Background in RF, spectrum management, spectrum sensing, software defined radios, propagation modeling, signal processing, or related DoD domains
  • Cybersecurity awareness in the context of AI systems and DoD environments
  • Experience with cloud-hosted LLM APIs as a secondary deployment target
  • Active Secret (or Higher) Clearance
Peraton Overview

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can't be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we're keeping people around the world safe and secure.

Target Salary Range$112,000 - $179,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual's experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.EEOEEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.Employment Type: FULL_TIME

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About Peraton

Sourced by ZipRecruiter

At Peraton, we re at the forefront of delivering the next big thing every day. We re the partner of choice to help solve some of the world s most daunting challenges, delivering bold, new solutions to keep people around the world safer and more secure.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Herndon, VA, US

Year founded

2017