AI Architect - GTM Systems

Accountabilities:: 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: 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. Benefits: Fully remote position available across Canada. Annual base salary range of $135,575–$175,450 USD , with actual compensation varying based on location, experience, skills, and job-related qualifications. Eligibility for an initial Restricted Stock Unit (RSU) grant with no vesting cliff, subject to applicable plan terms. Potential ongoing equity refresh opportunities based on performance and applicable plan conditions. Performance-based bonus or variable compensation as part of the broader total rewards package. Flexible, employee-led remote working model. Professional development stipend. Comprehensive health benefits. Parental leave programs. Opportunities for career development and technical growth. Exposure to advanced AI, agentic systems, cloud infrastructure, enterprise integrations, and GTM technology. Opportunity to work with multidisciplinary teams and senior business stakeholders on high-impact initiatives. Inclusive and collaborative environment focused on innovation, technical excellence, and continuous learning.