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Showpad is seeking a GTM Engineer to design, build, and deploy AI agents and AI-enabled workflows that drive business outcomes in a B2B SaaS environment. This role bridges Go-To-Market processes with advanced cloud and AI technologies, requiring deep expertise across multiple domains.
Key Responsibilities:
- Develop and implement end-to-end GTM strategies and processes within B2B SaaS, translating business problems into technology solutions.
- Create and optimize multi-system workflows and automations using REST APIs and event-driven integration patterns.
- Design and deploy serverless applications and event-driven architectures on AWS.
- Build and integrate AI agents and workflows using Amazon and Claude/Anthropic models with approved business systems.
- Collaborate with stakeholders to ensure AI agents and workflows meet standards for accuracy, reliability, scalability, and security.
- Contribute to developing standards for AI agent lifecycle management and observability.
This is a hands-on technical role requiring expertise in GTM domain knowledge, workflow automation, AWS cloud engineering, and modern AI/LLM technologies. The ideal candidate will have experience translating complex business requirements into scalable, secure, and measurable solutions.
Requirements:
- 6+ years of direct experience with GTM processes and systems in B2B SaaS or technology environments.
- Strong understanding of end-to-end Lead-to-Revenue and customer lifecycle processes, including Sales, Marketing, Customer Success, and Revenue Operations workflows.
- Demonstrated ability to work with business stakeholders and translate requirements into process and technology solutions.
- Strong understanding of REST APIs, webhooks, JSON, OAuth, authentication, and event-driven integration patterns.
- Experience designing multi-system workflows and automations; familiarity with workflow orchestration technologies (Zapier, n8n, Workato, Make, Tray.io, or comparable).
- Hands-on experience with AWS Lambda, serverless patterns, AWS Step Functions, Amazon EventBridge, and event-driven architecture.
- Experience with Amazon Bedrock or building applications using foundation-model APIs.
- Familiarity with API Gateway, CloudWatch, IAM, Secrets Manager, S3, queues, databases, and cloud security practices.
- Hands-on experience with Claude/Anthropic and/or other leading foundation models.
- Practical knowledge of prompt engineering, structured outputs, tool/function calling, agentic workflows, and AI orchestration.
- Understanding of Model Context Protocol (MCP) concepts and MCP-enabled tools (prior MCP experience beneficial but not required).
- Knowledge of RAG concepts, human-in-the-loop patterns, model evaluation, AI observability, and AI security/guardrails.
- Ability to evaluate when low-code/no-code automation is appropriate versus custom development.
- Experience with web scraping, browser automation, or data extraction is beneficial.
- Ability to quickly learn and evaluate emerging automation and AI technologies.
