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Ai Integration Engineer Jobs in Boston, MA (NOW HIRING)

Klaviyo

Senior AI Engineer

Boston, MA · On-site

$113K - $155K/yr

They are seeking a Senior AI Engineer to design, build, and scale production-grade LLM integrations and AI-powered automation tools, focusing on applied AI research and full-stack software ...

Klaviyo

Senior AI Application Engineer

Boston, MA · On-site

They are seeking a Senior AI Application Engineer to design, build, and scale production-grade LLM ... Design robust, scalable API integrations between AI models and internal systems such as HRIS, ...

Laminar

PLC Integration Engineer (PIE)

Somerville, MA · On-site

$80K - $110K/yr

Powered by our Laminar AI Co-pilot models and state-of-the-art sensors, our solutions optimize facility performance across various processes, including process manufacturing, production, water ...

Laminar

PLC Integration Engineer (PIE)

Somerville, MA · On-site

Powered by our Laminar AI Co-pilot models and state-of-the-art sensors, our solutions optimize facility performance across various processes, including process manufacturing, production, water ...

Laminar

PLC Integration Engineer (PIE)

Somerville, MA · On-site

$80K - $110K/yr

Powered by our Laminar AI Co-pilot models and state-of-the-art sensors, our solutions optimize facility performance across various processes, including process manufacturing, production, water ...

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Showing results 21-40

All JobsAi Integration Engineer JobsAi Integration Engineer Jobs in Boston, MA

Ai Integration Engineer information

See Boston, MA salary details

$48.3K

$135K

$188.5K

How much do ai integration engineer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for ai integration engineer in Boston, MA is $135,005.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $152,100.00 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 Boston, MA?

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

What job categories do people searching Ai Integration Engineer jobs in Boston, MA look for?

The top searched job categories for Ai Integration Engineer jobs in Boston, MA are:

What cities near Boston, MA are hiring for Ai Integration Engineer jobs?

Cities near Boston, MA with the most Ai Integration Engineer job openings:

Ai Integration Engineer jobs near you
Infographic showing various Ai Integration Engineer job openings in Boston, MA as of June 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $135,013 per year, or $64.9 per hour.

Senior AI Engineer

Klaviyo

Boston, MA • On-site

$113K - $155K/yr

Full-time

Re-posted 15 days ago

Job description

Job Summary:
Klaviyo is a company that empowers creators to own their destiny by making first-party data accessible and actionable. They are seeking a Senior AI Engineer to design, build, and scale production-grade LLM integrations and AI-powered automation tools, focusing on applied AI research and full-stack software engineering.
Responsibilities:
• Design and build LLM-powered applications: Architect and develop production-grade systems leveraging large language models (GPT-4, Claude, Mistral, Llama) for internal automation, knowledge retrieval, and intelligent workflow assistance.
• Build and maintain AI integration pipelines: Design robust, scalable API integrations between AI models and internal systems such as HRIS, ticketing, CRM, and knowledge bases, ensuring reliability, low latency, and high availability.
• Develop full-stack AI features end-to-end: Own the complete development of AI features across the stack from backend model orchestration and API layers to frontend interfaces that make AI accessible to non-technical employees.
• Architect and manage CI/CD pipelines for AI systems: Build and maintain automated deployment pipelines for AI models and services, including model evaluation frameworks, A/B testing infrastructure, and safe rollout strategies.
• Implement RAG and retrieval systems: Design and build retrieval-augmented generation systems grounded in Klaviyo internal knowledge, ensuring accuracy, relevance, and up-to-date responses at scale.
• Evaluate and fine-tune AI models: Lead benchmarking, evaluation, and fine-tuning of foundation models for Klaviyo use cases, including prompt engineering and parameter-efficient fine-tuning techniques.
• Establish AI engineering best practices: Define coding standards, testing frameworks, and architectural patterns for AI development at Klaviyo, enabling the team to ship reliable AI features consistently.
• Build AI observability and monitoring tooling: Instrument AI systems with latency monitoring, output quality evaluation, hallucination detection, cost dashboards, and production alerting.
• Collaborate with Product and Data Science: Work closely with PMs, data scientists, and ML engineers to translate requirements into technical implementations, maintaining a tight feedback loop between experimentation and production.
• Drive security and compliance in AI systems: Ensure AI integrations follow data privacy best practices, implement guardrails for sensitive data handling, and maintain compliance with Klaviyo security and governance standards.
Qualifications:
Required:
• 3+ years of software engineering experience, with at least 2 years focused on building AI, ML, or LLM-powered systems in production.
• Deep expertise with large language models such as OpenAI, Anthropic, Mistral, or Llama, and experience integrating them into production applications via API.
• Strong full-stack engineering skills across Python (FastAPI, Flask, or Django) and TypeScript or JavaScript, with experience in modern frontend frameworks.
• Proven experience designing and building CI/CD pipelines for software or ML systems using tools such as GitHub Actions, Jenkins, or CircleCI.
• Experience with RAG systems, vector databases (Pinecone, Weaviate, pgvector), and embedding models.
• Proficiency with cloud infrastructure (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and infrastructure-as-code tools such as Terraform or Pulumi.
• Experience with prompt engineering, model evaluation frameworks, and LLM observability tools such as LangSmith or Weights and Biases.
Company:
Klaviyo is an automation and email platform designed to help grow businesses. Founded in 2012, the company is headquartered in Boston, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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