Canada D&A A2 AI Engineer

Responsibilities

Design, build, and operate AI-driven data ingestion frameworks, real-time processing solutions, ETL pipelines, and machine learning applications across the full stack. Deploy and support production systems, operationalize open-source AI tools, uphold data governance, and contribute to complex projects in line with ethical guidelines.

Requirements

Requires a bachelor's or master's degree in Computer Science and 2–4 years of software engineering experience. Candidates should have strong programming skills, knowledge of machine learning, deep learning, and NLP, experience building backend services, full-stack development proficiency, and strong communication skills.

Skills

• Python
• Java
• C++
• Machine Learning
• Deep Learning
• Natural Language Processing
• FastAPI
• Flask
• Django
• React
• Angular
• Apache Kafka
• Apache Spark
• ETL
• Data Pipelines
• TensorFlow

About this role

 Roles & responsibilities 
Here are some of the key responsibilities of a Software Engineer (A2) 
Design and develop AI-driven data ingestion frameworks and real-time processing
solutions that enhance data analysis and machine learning capabilities across
the full technology stack 
Deploy, maintain, and support application codes and machine learning models in
production environments, ensuring seamless integration with front-end and
back-end systems.
Create and enhance AI solutions that facilitate seamless integration and flow of
data across the data ecosystem, enabling advanced analytics and insights for end
users.
Conduct business analysis to gather requirements and develop ETL processes,
scripts, and machine learning pipelines that meet technical specifications and
business needs, utilizing both server-side and client-side technologies.
Develop real-time data ingestion and stream-analytic solutions utilizing
technologies such as Kafka, Apache Spark (SQL, Scala, Java), Python, and cloud
platforms to support AI applications. Utilize multiple programming languages and
tools, including Python, Spark, Hive, Presto, Java, and JavaScript frameworks
(e.g., React, Angular) to build prototypes for AI models and evaluate their
effectiveness and feasibility.
Develop application systems that adhere to standard software development
methodologies, ensuring robust design, programming, backup, and recovery
processes to deliver high-performance AI solutions across the full stack.
Provide system support as part of a team rotation, collaborating with other
engineers to resolve issues and enhance system performance, including both
front-end and back-end

Operationalize open-source AI and data-analytic tools for enterprise-scale
applications, ensuring they align with organizational needs and user interfaces.
Ensure compliance with data governance policies by implementing and validating
data lineage, quality checks, and data classification in AI projects.
Understand and follow the company’s software development lifecycle to
effectively develop, deploy, and deliver AI solutions.
Design and develop AI frameworks leveraging open-source tools and advanced data
processing frameworks, integrating them with user-facing applications. Lead the
design and execution of complex AI projects, ensuring alignment with ethical
guidelines and principles under the guidance of senior team members.
 

RESPONSIBILITIES

 Roles & responsibilities 
Here are some of the key responsibilities of a Software Engineer (A2) 
Design and develop AI-driven data ingestion frameworks and real-time processing
solutions that enhance data analysis and machine learning capabilities across
the full technology stack 
Deploy, maintain, and support application codes and machine learning models in
production environments, ensuring seamless integration with front-end and
back-end systems.
Create and enhance AI solutions that facilitate seamless integration and flow of
data across the data ecosystem, enabling advanced analytics and insights for end
users.
Conduct business analysis to gather requirements and develop ETL processes,
scripts, and machine learning pipelines that meet technical specifications and
business needs, utilizing both server-side and client-side technologies.
Develop real-time data ingestion and stream-analytic solutions utilizing
technologies such as Kafka, Apache Spark (SQL, Scala, Java), Python, and cloud
platforms to support AI applications. Utilize multiple programming languages and
tools, including Python, Spark, Hive, Presto, Java, and JavaScript frameworks
(e.g., React, Angular) to build prototypes for AI models and evaluate their
effectiveness and feasibility.
Develop application systems that adhere to standard software development
methodologies, ensuring robust design, programming, backup, and recovery
processes to deliver high-performance AI solutions across the full stack.
Provide system support as part of a team rotation, collaborating with other
engineers to resolve issues and enhance system performance, including both
front-end and back-end

Operationalize open-source AI and data-analytic tools for enterprise-scale
applications, ensuring they align with organizational needs and user interfaces.
Ensure compliance with data governance policies by implementing and validating
data lineage, quality checks, and data classification in AI projects.
Understand and follow the company’s software development lifecycle to
effectively develop, deploy, and deliver AI solutions.
Design and develop AI frameworks leveraging open-source tools and advanced data
processing frameworks, integrating them with user-facing applications. Lead the
design and execution of complex AI projects, ensuring alignment with ethical
guidelines and principles under the guidance of senior team members.
 

Mandatory  technical & functional skills
Technical Skills: Strong proficiency in on Python, Java, C++ and , as well as
familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch).
In depth knowledge on ML, Deep Learning and NLP algorithms.
Strong programming skills hands on experience in building backend services with
frameworks like FastAPI, Flask, Django, etc.
Full-Stack Development: Proficiency in front-end and back-end technologies,
including JavaScript frameworks (e.g., React, Angular), to build and integrate
user interfaces with AI models and data solutions.
Data Integration: Develop and maintain data pipelines for AI applications,
ensuring efficient data extraction, transformation, and loading (ETL) processes
Strong oral and written communication skills with the ability to communicate
technical and non-technical concepts to peers and stakeholders
 

QUALIFICATIONS

 This role is for you if you have  the below
Educational qualifications

Bachelor’s / Master’s degree in Computer Science

Work experience
2 to 4 years of Software Engineering experience
 

About KPMG Global Services

Business Consulting and Services · 10,001+ employees · headquartered in Gurugram, Haryana