Quick Summary
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Architect - GTM Systems based in Canada.
This senior individual contributor role will define the technical vision for AI-powered Go-To-Market systems and automation.
You will architect, prototype, and establish scalable patterns across low-code platforms, enterprise integrations, and custom AI agents.
The role combines hands-on engineering with architectural leadership, requiring the ability to move from strategic discussions to working prototypes.
You will partner with GTM engineering, Sales Operations, business technology, and executive stakeholders to turn business objectives into technical roadmaps.
The position will shape standards for agentic AI, LLM orchestration, integrations, governance, observability, and responsible AI.
You will influence how complex GTM workflows are designed, evaluated, automated, and operated at enterprise scale.
This is a fully remote opportunity for an experienced technical leader who enjoys setting architectural direction while remaining deeply hands-on.
- Define and own the technical vision and architecture strategy for AI-powered GTM systems, covering both low-code automation and custom agentic AI solutions.
- Establish reference architectures, design patterns, and decision frameworks that guide technology choices across the GTM engineering organization.
- Determine when to use low-code platforms such as Workato, MuleSoft, and Salesforce Flow versus custom AI and software engineering solutions.
- Lead the architecture of complex GTM systems involving multi-system integrations, agentic workflows, real-time event processing, and cross-platform data orchestration.
- Design integration strategies across platforms such as Salesforce, NetSuite, Marketo, and custom data stores, including APIs, event contracts, and data models.
- Evaluate, select, and drive adoption of emerging AI tools, frameworks, and platforms while balancing innovation, risk, operational requirements, and technical debt.
- Serve as a technical authority on LLM orchestration, including prompt safety, retrieval-augmented generation, model context management, tool calling, multi-agent coordination, and responsible AI practices.
- Establish governance, extensibility, and operational standards that enable safe and scalable low-code automation.
- Partner with senior GTM stakeholders to translate strategic business objectives into architectural roadmaps with defined trade-offs, timelines, and success criteria.
- Conduct architecture reviews, provide structured technical feedback, identify systemic risks, and promote continuous improvement in engineering practices.
- Develop internal technical thought leadership through architecture decision records, white papers, engineering documentation, and knowledge-sharing initiatives.
- Mentor engineers and contribute to raising the technical standards and architectural capabilities of the wider organization.
Requirements
~2 min read- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- 10+ years of software engineering experience with a proven record of building and deploying production-grade backend systems.
- At least 3 years of experience in a Technical Lead or comparable technical leadership role.
- Demonstrated hands-on experience building and deploying AI agents used by real end users, with the ability to explain the problem, architecture, implementation, and outcome of a specific agent.
- Strong practical knowledge of LLM orchestration and agentic frameworks such as LangGraph, LangChain, CrewAI, LlamaIndex, or equivalent technologies.
- Experience designing and implementing RAG systems, including vector databases, retrieval strategies, chunking approaches, and embedding pipelines.
- Strong backend engineering fundamentals with Python and/or Node.js and experience with FastAPI or equivalent frameworks.
- Experience with asynchronous and event-driven architecture patterns.
- Experience with AWS and cloud-native services such as Bedrock, Lambda/serverless, SQS, SNS, EventBridge, or equivalent technologies.
- Strong communication skills and the ability to work directly with non-technical stakeholders to understand requirements and translate business objectives into technical solutions.
- Strong architectural judgment and the ability to balance low-code, custom development, automation, governance, scalability, and maintainability.
- Experience building evaluation and observability capabilities for LLM-powered systems, such as LangFuse, tracing solutions, benchmark suites, or custom evaluation frameworks, is desirable.
- Familiarity with sales, deal desk, finance, or revenue operations workflows is desirable.
- Experience with FastMCP, LiteLLM, Model Context Protocol (MCP), or production multi-agent systems is desirable.
- Familiarity with Salesforce as a data source and understanding of where relevant GTM data resides is desirable.
- Experience in an AI-for-GTM or RevOps environment, or experience transitioning from RevOps into AI engineering, is desirable.
- Experience mentoring engineers or contributing to technical hiring is desirable.
- Knowledge of prompt engineering and model behavior across different LLM providers, including OpenAI and Anthropic/Claude, is desirable.
- Full-stack development experience involving custom applications, AWS Bedrock, Node.js, Python, and serverless technologies is desirable.
What We Offer
~2 min readLocation & Eligibility
Listing Details
- Posted
- September 23, 2026
- First seen
- September 27, 2026
- Last seen
- September 27, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 68%
- Scored at
- September 27, 2026
Signal breakdown
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