Senior SR&ED Consultant (Software Engineer)

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KPMG’s Tax Incentives Practice helps innovative organizations access federal and provincial innovation funding programs, including the Scientific Research and Experimental Development (SR&ED) program.

As software, AI and technology organizations continue to invest in increasingly complex research and development, our team is seeking a  Senior Consultant with a strong software engineering background, systems-level technical fluency, and hands-on experience using modern AI development tools.

In this role, you will work directly with software engineers, architects, CTOs, technical leaders and KPMG tax professionals to understand complex development activities, identify technological uncertainty and experimental development, analyze supporting technical evidence, and contribute to the preparation and delivery of well-supported SR&ED claims.

The role requires the ability to move beyond what a development team built and understand  why the underlying technical problem was difficult, why established approaches were insufficient, what alternatives were investigated, and what was learned through the development process .

• Analyze complex software and technology projects to assess eligibility under the SR&ED program, with particular focus on identifying technological uncertainty, systematic investigation and technological advancement.
• Conduct structured, technically grounded interviews with software engineers, architects, CTOs, product managers and other technical leaders to understand development activities and uncover experimental work that may not initially be described as research and development.
• Analyze software architectures, technology stacks and engineering decisions to understand the technical constraints underlying development activities.
• Investigate areas such as architectural limitations, scalability and performance constraints, distributed-system behaviour, data-model challenges, integration complexity, failure modes, unexpected results, workarounds and iterative refinements.
• Evaluate why established technologies, architectures, frameworks or development approaches were insufficient under the technical constraints faced by the development team.
• Understand and evaluate modern software environments involving cloud infrastructure, distributed systems, databases, APIs, data pipelines, AI and machine learning, security, identity, testing, deployment and related technologies.
• Review and synthesize technical evidence from Jira, Azure DevOps, GitHub, GitLab, architecture and design documentation, testing systems, engineering records and other relevant sources.
• Prepare and review high-quality technical project narratives and supporting documentation that clearly articulate technological uncertainties, hypotheses, experimental work, results and technological advancements.
• Translate complex software concepts, architectural decisions and engineering trade-offs into clear, concise and defensible technical documentation.
• Identify gaps, inconsistencies and weaknesses in technical positions and supporting evidence and work with clients to resolve them.
• Connect technical development activities with the personnel, resource allocations and expenditures associated with SR&ED claims.
• Lead technical workstreams on client engagements and coordinate deliverables with internal and external stakeholders.
• Collaborate with KPMG tax professionals and multidisciplinary teams to develop comprehensive and well-supported SR&ED claims.
• Support clients through CRA reviews and other SR&ED-related inquiries.
• Manage multiple engagements and competing priorities while maintaining a high standard of technical quality.
• Stay current with developments in software engineering, artificial intelligence, development methodologies and emerging technologies.

AI-Native Technical Capability

Successful candidates should have  hands-on experience building software and solving technical problems using AI coding agents and AI-enabled development tools — beyond prompt writing or basic chatbot use .

This may include experience with technologies such as:

• Claude Code;
• ChatGPT;
• OpenAI Codex;
• Cursor;
• GitHub Copilot;
• Model Context Protocol (MCP);
• custom skills and subagents;
• automation agents; and
• agentic or multi-agent development workflows.

Candidates should be comfortable using these technologies to work with code and repositories, analyze technical information, create or modify scripts, automate workflows, connect tools and data sources, and develop reusable AI-assisted processes.

Experience designing workflows where AI systems can  gather context, use tools, perform work, evaluate results and iterate is particularly relevant.

Within the SR&ED practice, these capabilities may be applied to:

• understand unfamiliar technologies and architectures;
• navigate and analyze large technical repositories;
• synthesize engineering documentation and development records;
• analyze Jira, Git and other engineering evidence;
• identify technical constraints, experiments, failures and iterative development;
• prepare targeted technical interview strategies;
• identify inconsistencies and evidence gaps across multiple sources;
• analyze structured and unstructured client data;
• develop scripts and lightweight analytical tools; and
• automate repeatable technical analysis and engagement workflows.

AI tools are intended to augment technical analysis and professional judgment, not replace them. Successful candidates will be expected to critically evaluate AI-generated outputs and remain accountable for the underlying technical analysis and conclusions.

• Bachelor’s degree in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering, Data Science or a related technical discipline.
• Professional experience in software development, software engineering, systems architecture, technical consulting or a research and development environment.
• Strong systems-level technical fluency and the ability to understand and evaluate software architectures, technology stacks and design decisions as explained by CTOs, architects and development teams.
• Strong understanding of modern software engineering concepts, including software architecture, databases, cloud technologies, APIs, distributed systems, data pipelines, monitoring, testing and deployment.
• Hands-on experience building software using modern development languages, frameworks and tooling.
• Hands-on experience with AI coding agents and AI-enabled development tools such as Claude Code, Cursor, GitHub Copilot, Codex or comparable technologies.
• Experience with agentic technologies such as MCP, custom skills or subagents, automation agents or multi-agent workflows is considered an asset.
• Ability to rapidly understand unfamiliar technologies and technical domains.
• Demonstrated ability to conduct technically grounded interviews and identify underlying engineering constraints, limitations, failure modes, experimental approaches and iterative refinements.
• Strong analytical skills and the ability to distinguish routine software development from technical work involving unresolved technological challenges.
• Ability to translate complex technical activities into clear and credible technical documentation.
• Strong verbal and written communication skills, including the ability to communicate effectively with both technical and non-technical stakeholders.
• Strong organizational skills and the ability to manage multiple client engagements and competing priorities in a deadline-driven environment.
• Demonstrated initiative, ownership and sound professional judgment.
• Knowledge of SR&ED or other innovation funding programs is considered an asset.

Keys to Your Success

KP MG professionals are expected to approach their work with integrity, curiosity, collaboration and a commitment to quality.

For this role, success will also depend on your ability to:

• Think technically: Understand systems at the architectural level and identify the engineering constraints that materially affected development.
• Ask effective questions: Conduct persistent technical interviews that move beyond features and business objectives to uncover the underlying technological challenges.
• Think in systems: Understand how architecture, data, infrastructure, software components and operational constraints interact.
• Exercise judgment: Distinguish between routine engineering and work involving genuine technological uncertainty and experimental development.
• Learn quickly: Develop sufficient understanding of unfamiliar technologies to engage credibly with experienced technical teams.
• Work AI-natively: Use modern AI development tools as part of your normal technical workflow and continuously identify opportunities to improve how work is performed.
• Take ownership: Identify information gaps, technical risks and next steps and proactively work with clients and engagement teams to address them.
• Communicate clearly: Explain complex technical matters accurately and concisely without unnecessary technical or SR&ED terminology.

Who Will Thrive in This Role

• You will thrive in this role if you enjoy understanding how complex technology works and are motivated to get beneath the surface description of a development project.
• You are comfortable discussing architecture and engineering decisions with CTOs, architects and development teams, while continuing to ask questions until you understand the technical constraints that drove the work.
• You are intellectually curious and able to move from:

Feature → Implementation → Technical Obstacle → Underlying Constraint → Investigation → Technological Advancement

• You are also an active user of modern AI development tools and are interested in how coding agents, automation and agentic workflows can improve the way technical work is performed.
• Previous SR&ED experience is valuable, but deep SR&ED experience is not required. The successful candidate will bring the  technical foundation, curiosity, judgment and learning agility required to develop strong SR&ED expertise within KPMG.
• This role provides an opportunity to work at the intersection of  software engineering, artificial intelligence, technical consulting and SR&ED , while working directly with organizations developing some of Canada’s most complex and innovative technologies.

KPMG BC Region Pay Range Information  

The expected base salary range for this position is $65,000 to $99,000 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program. 

Providing you with the support you need to be at your best

Integrity , we do what is right |  Excellence , we never stop learning and improving |  Courage , we think and act boldly | Together , we respect each other and draw strength from our differences |  For Better , we do what matters

KPMG in Canada is a proud equal opportunities employer and we are committed to creating a respectful, inclusive and barrier-free workplace that allows all of our people to reach their full potential. A diverse workforce is key to our success and we believe in bringing your whole self to work. We welcome all qualified candidates to apply and hope you will choose KPMG in Canada as your employer of choice.

Adjustments and accommodations throughout the recruitment process

At KPMG, we are committed to fostering an inclusive recruitment process where all candidates can be themselves and excel. We aim to provide a positive experience and are prepared to offer adjustments or accommodations to help you perform at your best. Adjustments (informal requests), such as extra preparation time or the option for micro breaks during interviews, and accommodations (formal requests), such as accessible communication supports or technology aids, are tailored to individual needs and role requirements. You will have an opportunity to request an adjustment or accommodation at any point throughout the recruitment process. If you require support, please contact KPMG’s Employee Relations Service team by calling View phone number on careers.kpmg.ca.

AI Usage

We embrace the use of artificial intelligence (AI) to enhance the candidate experience and streamline our recruitment processes. AI tools may help with organizing applications or surfacing relevant qualifications. However, no hiring decisions are made using AI. Every hiring decision is made by our hiring managers and recruitment professionals, who are equipped with training that empowers them to use these tools responsibly. AI technologies used in our recruitment process undergo detailed risk assessments, including security and privacy requirements, that align with KPMG’s Trusted AI framework.

We believe technology should empower human judgment, not replace it. It’s one of the many ways we’re delivering on our vision of being a technology-first, people-driven firm.