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Ai Integration Engineer Jobs in Connecticut (NOW HIRING)

Starhired

Electro-Mechanical Engineer

East Windsor, CT · On-site

AI integration and product automation * You need SCCR and UL 508/A experience * Other tasks as assigned. What you will get as an Electro-Mechanical Engineer: * Competitive Pay * health, dental ...

New

Deloitte

AI Engineer Consultant

Hartford, CT · Hybrid

You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non ...

Deloitte

AI Engineer Consultant

Stamford, CT · Hybrid

You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non ...

EMCOR Group, Inc.

AI Security Engineer

Norwalk, CT · On-site

$134 - $171/hr

Job Summary EMCOR Group, Inc. seeks an AI Security Engineer who will be responsible for securing ... Conduct threat modeling for AI systems and integrations and translate threats into technical ...

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All JobsAi Integration Engineer JobsAi Integration Engineer Jobs in Connecticut

Ai Integration Engineer information

See Connecticut salary details

$42.3K

$118.2K

$165K

How much do ai integration engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for ai integration engineer in Connecticut is $118,221.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,900.00 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 Connecticut?

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

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

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

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

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

Ai Integration Engineer jobs near you
Infographic showing various Ai Integration Engineer job openings in Connecticut as of August 2026, with employment types broken down into 62% Full Time, 19% Part Time, and 19% Contract. Highlights an 100% In-person job distribution, with an average salary of $118,221 per year, or $56.8 per hour.

Software Integration Engineer, Laboratory Automation

Thermo Fisher Scientific

Groton, CT

$103K - $139K/yr

Full-time

Posted 7 days ago

Thermo Fisher Scientific rating

7.8

Company rating: 7.8 out of 10

Based on 428 frontline employees who took The Breakroom Quiz

175th of 543 rated manufacturers

Job description

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

As part of the Thermo Fisher Scientific team, you'll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer.

As a Software Integration Engineer, you will develop software integrations connecting laboratory instruments with Thermo Scientific™ Momentum Software, AI-enabled scientific applications, and customer digital workflows. You will play a key role in enabling intelligent laboratory automation by integrating software platforms, laboratory instruments, and AI-driven workflows into scalable customer solutions.

[Key Competencies]

  • Customer-focused with strong analytical and problem-solving skills.
  • Excellent communication and collaboration across customers and cross-functional teams.
  • Self-driven with the ability to manage multiple priorities while delivering high-quality software.


[Key Responsibilities]

  • Design, develop, test, and maintain custom Momentum™ SDK drivers for laboratory instrument integration.
  • Develop reliable software interfaces between Momentum and third-party laboratory instruments using standard communication protocols and APIs.
  • Integrate laboratory instruments into automated workflows while ensuring software quality through validation, testing, and deployment support.
  • Translate customer workflow requirements into scalable software integration solutions through close collaboration with customers and cross-functional teams.
  • Troubleshoot software, communication, and hardware integration issues during development and customer implementation.
  • Develop technical documentation and reusable software components that support standardized integration and long-term maintainability.
  • Collaborate with global engineering teams to ensure compliance with Momentum SDK standards and software development best practices.
  • Support customer demonstrations, Proof-of-Concept (PoC) activities, and continuous improvement of integration frameworks and engineering standards.
  • Integrate AI-enabled scientific applications and software services with laboratory automation workflows to support intelligent laboratory operations.
  • Collaborate with AI software engineers to enable seamless interaction between laboratory instruments, workflow platforms, and AI-powered applications.

[Qualifications]

Education

  • Bachelor’s degree in computer science, Software Engineering, Computer Engineering, Electrical Engineering, or a related discipline.

Experience

  • Minimum 7+ years of software development experience.
  • Experience with object-oriented software development, laboratory or industrial system integration, and software platform integration.
  • Experience in software validation, testing, and troubleshooting.

[Knowledge, Skills, Abilities]

  • Strong programming skills in C# and .NET, Visual Studio, experience integrating software APIs and AI-enabled applications.
  • Knowledge of communication protocols including TCP/IP, REST APIs, Serial (RS-232/RS-485), OPC-UA, XML/JSON and software integration architectures supporting laboratory automation and AI workflows.
  • Software debugging, unit testing, and version control (Git/Azure DevOps)
  • Strong analytical, problem-solving, and debugging skills.
  • Excellent communication and collaboration skills with customers and cross-functional teams.
  • Business-level Korean and English communication skills.

[Preferred Qualifications]

  • Experience with biotechnology, life sciences, laboratory automation, research, or scientific software environments is highly desirable.
  • Experience integrating AI-enabled applications or digital laboratory platforms into laboratory automation workflows.
  • Experience developing laboratory instrument drivers or device control software.
  • Experience with Thermo Scientific™ Momentum, laboratory automation platforms, or scientific instrumentation.
  • Knowledge of laboratory automation standards, robotics, and scientific workflows.
  • Experience with Git/Azure DevOps, Agile software development, and SDLC practices.

What Thermo Fisher Scientific employees say

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