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