<p><strong>Summary:</strong> We are seeking a skilled GTM Engineer to join our dynamic team. This role plays a critical part in designing, building, and deploying AI agents and AI-enabled workflows, leveraging advanced technologies to drive business outcomes in a B2B SaaS environment. The ideal candidate will have a strong background in GTM processes, workflow automation, AWS, cloud engineering, and AI technologies.</p> <p><strong>Responsibilities:</strong></p> <ul> <li>Develop and implement end-to-end GTM strategies and processes within a B2B SaaS environment.</li> <li>Create and optimize multi-system workflows and automations using REST APIs and event-driven integration patterns.</li> <li>Design and deploy serverless applications and event-driven architectures using AWS services.</li> <li>Build and integrate AI agents and workflows using Amazon, Claude/Anthropic models, and approved business systems.</li> <li>Collaborate with stakeholders to translate business problems into effective technology solutions.</li> <li>Ensure AI agents and workflows meet standards for accuracy, reliability, scalability, and security.</li> <li>Contribute to the development of standards for AI agent lifecycle management and observability.</li> </ul> <p><strong>Required Skills:</strong></p> <h2><strong>GTM & Business Experience</strong></h2> <ul> <li>6+ years of experience working directly with GTM processes and systems in a B2B SaaS or technology environment.</li> <li>Strong understanding of end-to-end Lead-to-Revenue and customer lifecycle processes.</li> <li>Demonstrated understanding of Sales, Marketing, Customer Success, and Revenue Operations workflows.</li> <li>Strong understanding of core SaaS commercial concepts and metrics.</li> <li>Experience translating business problems into process and technology solutions.</li> <li>Demonstrated ability to work directly with business stakeholders and challenge or refine requirements.</li> <li>Experience working across multiple GTM platforms and understanding cross-system dependencies.</li> </ul> <h2><strong>Workflow Automation & Integration</strong></h2> <ul> <li>Strong understanding of REST APIs, webhooks, JSON, OAuth, authentication, and event-driven integration patterns.</li> <li>Experience designing multi-system workflows and automations.</li> <li>Experience with workflow orchestration technologies.</li> <li>Ability to evaluate when low-code/no-code automation is appropriate versus custom development.</li> <li>Experience with platforms such as Zapier, n8n, Workato, Make, Tray.io, or comparable technologies is beneficial but not required.</li> <li>Experience with web scraping, browser automation, data extraction, or related technologies is beneficial.</li> <li>Ability to quickly learn and evaluate emerging automation and data acquisition technologies.</li> </ul> <h2><strong>AWS & Cloud Engineering</strong></h2> <ul> <li>Hands-on experience with AWS Lambda and serverless application patterns.</li> <li>Experience with AWS Step Functions or comparable workflow orchestration concepts.</li> <li>Experience with Amazon EventBridge and event-driven architecture.</li> <li>Experience with Amazon Bedrock or demonstrated experience building applications using foundation-model APIs.</li> <li>Familiarity with API Gateway, CloudWatch, IAM, Secrets Manager, S3, queues, databases, and related AWS services.</li> <li>Understanding of cloud security, permissions, monitoring, and production support practices.</li> </ul> <h2><strong>AI Agents & Agentic Orchestration</strong></h2> <ul> <li>Design, build, and deploy AI agents and AI-enabled workflows within the approved architecture.</li> <li>Use <strong>Amazon and Claude / Anthropic models</strong> for reasoning, classification, summarization, research, recommendations, and decision support.</li> <li>Build agentic workflows combining LLM reasoning with structured business data, APIs, deterministic rules, web-derived information, and approved tools.</li> <li>Integrate agents with approved business systems and data sources through available APIs, connectors, and <strong>Model Context Protocol (MCP) capabilities</strong>.</li> <li>Understand how to discover, configure, and use available MCP servers and tools within AI workflows.</li> <li>Evaluate when an existing MCP capability can simplify access to a system or data source rather than building a custom integration.</li> <li>Design prompts, context, structured outputs, tool/function calling, guardrails, and human-in-the-loop patterns.</li> <li>Determine when deterministic workflow logic should be used instead of an LLM or agent.</li> <li>Test agents and workflows for accuracy, reliability, security, latency, scalability, cost, and measurable business value.</li> <li>Contribute to standards for agent permissions, observability, evaluation, and lifecycle management.</li> </ul> <h2><strong>AI & LLM Technologies</strong></h2> <p>Candidates should have hands-on experience with or strong practical knowledge of:</p> <ul> <li><strong>Claude / Anthropic</strong> and/or other leading foundation models</li> <li>Prompt and context engineering</li> <li>Structured outputs</li> <li>Tool / function callin