AI Software Engineer

SS&C Technologies•Mississauga, ON

2d•CA$165,000 - CA$210,000•Hybrid

About The Position

SS&C is embarking on an exciting journey to reimagine software engineering through Artificial Intelligence, and we're looking for an experienced AI Engineer to help lead that transformation. As an AI Engineer, you will design, develop, and implement AI-enabled solutions that accelerate and automate activities across the entire application delivery lifecycle—from requirements analysis and solution design to software development, testing, production support, and operational excellence. This is a rare greenfield opportunity to help build and shape the future of AI-driven software delivery within our organization. You will work at the forefront of AI-assisted engineering, helping establish new practices, platforms, and automation capabilities that modernize how software is delivered and supported.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related discipline.
10+ years of hands-on software development experience in Java and Python.
Proven experience designing and delivering enterprise software applications.
Proven experience transforming software delivery from traditional SDLC methodologies to autonomous AI-driven Application Development Lifecycle (ADLC) platforms, leveraging AI agents to automate planning, implementation, testing, review, integration, and delivery.
Experience implementing AI-assisted development capabilities within software engineering teams.
Strong background in solution design, software development, testing, and production support.
Hands-on experience with Claude Code, GitHub Copilot
Practical experience applying AI to Software design, Development, Code review, Testing, Documentation, Troubleshooting, Understanding of Prompt engineering, RAG concepts, AI agents
Context management strategies
AI evaluation and validation techniques
Strong proficiency in programming languages Java and Python and software development frameworks.
Experience with Microservices, Event-driven architectures, Database design and integration, Secure coding practices
Strong understanding of SDLC methodologies, CI/CD pipelines, DevOps practices, Agile delivery approaches

Responsibilities

Partner closely with business stakeholders, architects, developers, QA teams, and technology leaders to identify opportunities where AI can drive meaningful productivity gains and improve software quality.
Using tools such as Claude Code and other AI-assisted development technologies, design and implement practical solutions that reduce manual effort, automate repetitive tasks, accelerate delivery, and enhance engineering outcomes.
Help evolve from traditional Software Development Life Cycle (SDLC) practices toward an AI-driven Application Development Lifecycle (ADLC), introducing intelligent automation and AI agents that support planning, development, testing, code reviews, troubleshooting, and operational support.
Design and implement AI-enabled workflows that improve developer productivity and software quality.
Leverage Claude Code and AI-assisted development tools to accelerate project deliverables from requirement analysis till Production activities.
Apply AI-assisted approaches throughout the application development lifecycle while maintaining engineering quality standards.
Contribute to the evolution of software delivery processes from traditional SDLC approaches toward AI-driven Application Development Lifecycle (ADLC) models.
Implement AI agents and automation capabilities that support: Planning, Development, Testing, Review, Integration, Deployment, Operational support.
Identify opportunities to reduce manual effort and repetitive engineering tasks through AI-driven automation.
Support production applications and assist with troubleshooting complex technical issues.
Use AI-assisted techniques to accelerate root cause analysis and incident resolution.
Create and maintain technical documentation, operational procedures, and knowledge artifacts.
Collaborate with operations and support teams to improve application stability and operational efficiency.
Work closely with Product Owners, Business Analysts, Architects, QA teams, and Developers throughout the delivery lifecycle.
Contribute to technical design discussions and implementation planning.