GTM Engineer

Role Overview

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.

What You Will Do

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.

Why It Might Be a Fit

The ideal candidate will have a strong background in GTM processes, workflow automation, AWS, cloud engineering, and AI technologies.

Requirements

• 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.
• 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.
• 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.
• 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.
• 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.