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Ai Integration Engineer Jobs in Calgary, AB (NOW HIRING)

We're seeking a Senior Data Engineer to join our Delivery Team. In this role, you'll design and ... Experience with AI/ML integration and data science workflows. * Knowledge of data cataloging and ...

We're seeking a Senior Data Engineer to join our Delivery Team. In this role, you'll design and ... Experience with AI/ML integration and data science workflows. * Knowledge of data cataloging and ...

NET Engineers to support a healthcare industry client on key software development initiatives. The ... integration solutions, maintaining and modernizing legacy systems, and implementing AI-driven ...

NET Engineers to support a healthcare industry client on key software development initiatives. The ... integration solutions, maintaining and modernizing legacy systems, and implementing AI-driven ...

E&P data management and integration * Cloud and platform infrastructure, data services, and developer tooling * AI-assisted analytics, search, and generative AI Technologies used vary by team and ...

E&P data management and integration * Cloud and platform infrastructure, data services, and developer tooling * AI-assisted analytics, search, and generative AI Technologies used vary by team and ...

... analysis, and explore AI-driven methods to improve algorithm tunning or improve development ... CI/CD integrations Employment Type: FULL_TIME

GHD is a global network of multi-disciplinary professionals providing clients with integrated ... The use of artificial intelligence (AI) in recruiting is just getting started and may be used ...

Basic Qualifications * 5+ years of hands-on experience in data engineering, data integration, or ... Experience working with AI-driven platforms, data infrastructure supporting AI/ML systems, or ...

Clio is the global leader in legal AI technology, empowering legal professionals and law firms of ... Designing API and integration layers for log data access, enabling self-service analytics and ...

Showing results 41-60

Ai Integration Engineer information

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 Calgary, AB?

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

What job categories do people searching Ai Integration Engineer jobs in Calgary, AB look for?

The top searched job categories for Ai Integration Engineer jobs in Calgary, AB are:

Infographic showing various Ai Integration Engineer job openings in Calgary, AB as of August 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Sr. Data Engineer

Bits In Glass

Calgary, AB โ€ข Remote

Full-time

Posted 5 days ago


Job description

Join a company that’s leading the way in AI and automation consulting. Our portfolio spans 10+ top technologies across business applications, data, process, cloud, and AI. At Bits In Glass, you’ll do meaningful work with a supportive, driven team that loves to collaborate and celebrate wins together. Whether you’re coding, consulting or bringing bold ideas to the table, you’ll tackle real business challenges, grow your skills, and make a BIG impact. 


Our growing team has earned global recognition as a Great Place to Work and received multiple industry partner awards—while keeping things fun and people-focused. If you’re looking to deepen your expertise and solve real-world problems, Bits In Glass could be the place for you. 


We’re seeking a Senior Data Engineer to join our Delivery Team. In this role, you’ll design and implement modern data architectures that enable our clients to make data-driven decisions. You’ll lead the strategy, design, and technical direction of scalable data ecosystems across cloud platforms — ensuring integration, performance, and compliance.

As a Senior Data Engineer, you’ll work closely with business stakeholders, data engineers, and analytics teams to design data solutions that align with client goals. 


Responsibilities: 

  • Design and implement end-to-end data architectures, including data lakes, data warehouses, and analytics platforms.
  • Define data integration and transformation strategies, ensuring scalability, security, and performance.
  • Collaborate with stakeholders to translate business requirements into technical solutions that support analytics, reporting, and AI initiatives.
  • Develop data models, ETL/ELT pipelines, and frameworks for structured and unstructured data.
  • Provide technical leadership and mentorship to data engineers and developers, promoting best practices in data management and governance.
  • Ensure compliance with data governance, security, and privacy standards across platforms.
  • Optimize existing data architectures and processes for improved performance and reliability.
  • Stay current with industry trends, cloud data services, and emerging technologies such as Databricks, Snowflake, Azure Synapse, and AWS Redshift.
  • Act as a trusted advisor to clients, guiding them on architecture decisions and best practices for data modernization.


Required Skills & Experience

  • 5+ years of experience in data architecture, data engineering, or analytics solution design.
  • Hands-on experience with data lake and warehouse technologies (e.g., Databricks, Snowflake, Redshift, Synapse).
  • Deep understanding of data modeling, data integration, and ETL/ELT design.
  • Proficiency in SQL and one or more programming languages (Pyspark/Python, Scala), particularly for complex data transformations and optimization within Spark
  • Solid understanding of data governance, security, and privacy best practices.
  • Proven experience in designing, implementing, and optimizing large-scale ingestion pipelines using Databricks Autoloader
  • Deep practical knowledge of building and managing reliable, self-managing ETL/ELT pipelines using Delta Live Tables
  • Experience  in building high-throughput, low-latency streaming data ingestion solutions using  Apache Kafka, Spark Structured Streaming, and Databricks Streaming
  • Extensive experience in successfully applying and enforcing the Medallion architecture (Bronze, Silver, Gold layers) within a Databricks environment
  • Experience in designing and implementing  CI/CD pipelines (using tools like Azure DevOps, GitHub Actions, GitLab CI) specifically tailored for Databricks workflows, notebooks, and cluster configurations, enabling automated deployment and testing
  • Experience in planning and executing data migration projects from traditional data warehouses into the Databricks Lakehouse
  • Strong working knowledge of at least one major cloud provider (AWS, Azure) regarding data storage, networking, and security concepts relevant to Databricks deployment.
  • Proven ability to engage with clients, present technical solutions, and communicate complex ideas clearly.
  • Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related field.
  • Excellent problem-solving, communication, and collaboration skills.

Nice to Have:

  • Experience with AI/ML integration and data science workflows.
  • Knowledge of data cataloging and metadata management tools.
  • Prior consulting or client-facing experience in a technology services firm.


BIG is a high growth Cloud Consulting firm with offices in Edmonton, Calgary, Toronto, Denver, India and the United Kingdom.  Our clients are in Canada, UK, India  and the US.  We are a team of experienced IT professionals who specialize in providing business value to organizations looking at leveraging modern platforms such as Pega, Appian, MuleSoft and Boomi. Our vast experience in the IT industry and our current track record in enterprise software development, allow us to provide a full range of services to our clients.  Bits In Glass helps organizations of all sizes to automate their businesses and leverage the power of the web and mobile technologies.