{"id":1696098,"url":"https://alion.io/job/kpmg-senior-sred-consultant-software-engineer","title":"Senior sr&ed consultant (software engineer)","company":{"id":1186989,"name":"KPMG Canada","domain":"kpmg.ca","url":"https://alion.io/company/kpmg-ca","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"iCIMS","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Vancouver, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":75000,"max_usd":133000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":190},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Azure DevOps","optional":false},{"name":"ChatGPT","optional":false},{"name":"Claude Code","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"GitLab","optional":false},{"name":"Jira","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"Azure","optional":true}],"status":"live","first_seen_at":"2026-09-12T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-09-12T00:00:00Z","board_verified":false,"closed_at":null,"days_open":39,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":39},"description":"Overview\n\nAt KPMG in Canada, our people bring their unique perspectives to Canada’s most important challenges. Here, you can build momentum that reaches beyond our business, develop skills for the future, and take ownership of your career with support at every stage. Join a firm where your career can make a difference.\n\nKPMG’s Tax Incentives Practice helps innovative organizations access federal and provincial innovation funding programs, including the Scientific Research and Experimental Development (SR&ED) program.\nAs 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.\n\nIn 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.\nThe 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.\n\nWhat you will do\n\nAnalyze 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.\nConduct 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.\nAnalyze software architectures, technology stacks and engineering decisions to understand the technical constraints underlying development activities.\nInvestigate 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.\nEvaluate why established technologies, architectures, frameworks or development approaches were insufficient under the technical constraints faced by the development team.\nUnderstand 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.\nReview and synthesize technical evidence from Jira, Azure DevOps, GitHub, GitLab, architecture and design documentation, testing systems, engineering records and other relevant sources.\nPrepare and review high-quality technical project narratives and supporting documentation that clearly articulate technological uncertainties, hypotheses, experimental work, results and technological advancements.\nTranslate complex software concepts, architectural decisions and engineering trade-offs into clear, concise and defensible technical documentation.\nIdentify gaps, inconsistencies and weaknesses in technical positions and supporting evidence and work with clients to resolve them.\nConnect technical development activities with the personnel, resource allocations and expenditures associated with SR&ED claims.\nLead technical workstreams on client engagements and coordinate deliverables with internal and external stakeholders.\nCollaborate with KPMG tax professionals and multidisciplinary teams to develop comprehensive and well-supported SR&ED claims.\nSupport clients through CRA reviews and other SR&ED-related inquiries.\nManage multiple engagements and competing priorities while maintaining a high standard of technical quality.\nStay current with developments in software engineering, artificial intelligence, development methodologies and emerging technologies.\n\nAI-Native Technical Capability\nSuccessful 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.\nThis may include experience with technologies such as:\nClaude Code;\nChatGPT;\nOpenAI Codex;\nCursor;\nGitHub Copilot;\nModel Context Protocol (MCP);\ncustom skills and subagents;\nautomation agents; and\nagentic or multi-agent development workflows.\nCandidates 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.\nExperience designing workflows where AI systems can gather context, use tools, perform work, evaluate results and iterate is particularly relevant.\nWithin the SR&ED practice, these capabilities may be applied to:\nunderstand unfamiliar technologies and architectures;\nnavigate and analyze large technical repositories;\nsynthesize engineering documentation and development records;\nanalyze Jira, Git and other engineering evidence;\nidentify technical constraints, experiments, failures and iterative development;\nprepare targeted technical interview strategies;\nidentify inconsistencies and evidence gaps across multiple sources;\nanalyze structured and unstructured client data;\ndevelop scripts and lightweight analytical tools; and\nautomate repeatable technical analysis and engagement workflows.\n\nAI 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.\n\nWhat you bring to the role\n\nBachelor’s degree in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering, Data Science or a related technical discipline.\nProfessional experience in software development, software engineering, systems architecture, technical consulting or a research and development environment.\nStrong 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.\nStrong understanding of modern software engineering concepts, including software architecture, databases, cloud technologies, APIs, distributed systems, data pipelines, monitoring, testing and deployment.\nHands-on experience building software using modern development languages, frameworks and tooling.\nHands-on experience with AI coding agents and AI-enabled development tools such as Claude Code, Cursor, GitHub Copilot, Codex or comparable technologies.\nExperience with agentic technologies such as MCP, custom skills or subagents, automation agents or multi-agent workflows is considered an asset.\nAbility to rapidly understand unfamiliar technologies and technical domains.\nDemonstrated ability to conduct technically grounded interviews and identify underlying engineering constraints, limitations, failure modes, experimental approaches and iterative refinements.\nStrong analytical skills and the ability to distinguish routine software development from technical work involving unresolved technological challenges.\nAbility to translate complex technical activities into clear and credible technical documentation.\nStrong verbal and written communication skills, including the ability to communicate effectively with both technical and non-technical stakeholders.\nStrong organizational skills and the ability to manage multiple client engagements and competing priorities in a deadline-driven environment.\nDemonstrated initiative, ownership and sound professional judgment.\nKnowledge of SR&ED or other innovation funding programs is considered an asset.\n\nKeys to Your Success\nKPMG professionals are expected to approach their work with integrity, curiosity, collaboration and a commitment to quality.\nFor this role, success will also depend on your ability to:\nThink technically: Understand systems at the architectural level and identify the engineering constraints that materially affected development.\nAsk effective questions: Conduct persistent technical interviews that move beyond features and business objectives to uncover the underlying technological challenges.\nThink in systems: Understand how architecture, data, infrastructure, software components and operational constraints interact.\nExercise judgment: Distinguish between routine engineering and work involving genuine technological uncertainty and experimental development.\nLearn quickly: Develop sufficient understanding of unfamiliar technologies to engage credibly with experienced technical teams.\nWork AI-natively: Use modern AI development tools as part of your normal technical workflow and continuously identify opportunities to improve how work is performed.\nTake ownership: Identify information gaps, technical risks and next steps and proactively work with clients and engagement teams to address them.\nCommunicate clearly: Explain complex technical matters accurately and concisely without unnecessary technical or SR&ED terminology.\nWho Will Thrive in This Role\nYou 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.\nYou 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.\nYou are intellectually curious and able to move from:\nFeature → Implementation → Technical Obstacle → Underlying Constraint → Investigation → Technological Advancement\nYou 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.\nPrevious 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.\nThis 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.\n\nKPMG BC Region Pay Range Information \nThe 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. \n\nProviding you with the support you need to be at your best\n\nOur Values, The KPMG Way\n\nIntegrity, 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\n\nKPMG 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.\n\nAdjustments and accommodations throughout the recruitment process\n\nAt KPMG, we are committed to fostering an inclusive recruitment process where all candidates can be themselves and excel. 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