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Ai Integration Engineer Jobs in New York (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 ...

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 ...

Integration Engineer

Manhattan, NY · On-site

$133.50 - $200.30/hr

By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we're ... Role Overview Harvey is seeking an Integrations Engineer, Enterprise Systems to build and maintain ...

Integration Engineer

New York, NY · On-site

$133K - $200K/yr

By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we're ... Role Overview Harvey is seeking an Integrations Engineer, Enterprise Systems to build and maintain ...

Integration Engineer

Manhattan, NY · On-site

$134 - $200/hr

By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we're ... Role Overview Harvey is seeking an Integrations Engineer, Enterprise Systems to build and maintain ...

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Showing results 1-20

Ai Integration Engineer information

See New York salary details

$48.7K

$136K

$189.8K

How much do ai integration engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for ai integration engineer in New York is $135,961.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,800.00 and $153,200.00 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 New York?

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

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

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

What cities in New York are hiring for Ai Integration Engineer jobs?

Cities in New York with the most Ai Integration Engineer job openings:

Infographic showing various Ai Integration Engineer job openings in New York as of August 2026, with employment types broken down into 63% Full Time, 20% Part Time, and 17% Contract. Highlights an 100% In-person job distribution, with an average salary of $135,961 per year, or $65.4 per hour.

Senior AI Integration Developer

Peraton

Red Bank, NJ • On-site

$112 - $179/hr

Other

Posted 24 days ago


Peraton rating

8.3

Company rating: 8.3 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

52nd of 226 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.

EEO

EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.

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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