Go-to-Market (GTM) Engineer

About the Role

We are seeking a highly technical Go-to-Market Engineer to bridge the gap between product, engineering, AI, and customer-facing teams. This role is ideal for someone who thrives at the intersection of software engineering, AI systems, automation, and customer implementation. You will design and deploy AI-powered workflows, build technical integrations, accelerate customer onboarding, and create scalable automation systems that directly impact revenue generation and product adoption.

Responsibilities

• Design, build, and maintain AI-powered GTM workflows using LLMs, agents, and automation platforms.
• Develop customer-facing technical solutions, prototypes, and proofs of concept.
• Build integrations between internal systems, APIs, CRMs, data warehouses, and AI platforms.
• Create scalable automation pipelines for lead qualification, enrichment, outreach, onboarding, and customer success.
• Engineer prompt chains, retrieval systems, evaluation frameworks, and agentic workflows.
• Analyze model behavior, debug inference failures, and optimize AI system performance.
• Implement observability, tracing, and monitoring for AI applications and production workflows.
• Work closely with Sales, Product, Customer Success, and Engineering teams to solve technical challenges.
• Translate customer requirements into robust technical architectures.
• Develop internal tooling that improves operational efficiency and GTM execution.

Required Qualifications

• 1–3 years of experience in Software Engineering, Solutions Engineering, AI Engineering, Developer Relations, or a related technical role.
• Strong proficiency in Python and modern software development practices.
• Experience building AI applications using LLM APIs and agent frameworks.
• Deep understanding of prompt engineering, structured outputs, function/tool calling, and retrieval-augmented generation (RAG).
• Experience designing and debugging complex AI workflows and automation systems.
• Familiarity with API development, REST/GraphQL integrations, webhooks, and event-driven architectures.
• Strong understanding of data processing, ETL pipelines, and workflow orchestration.
• Experience with SQL and modern databases.

Preferred / Niche Technical Skills

• AI orchestration frameworks: LangGraph, LangChain, LlamaIndex, DSPy, Haystack, CrewAI, PydanticAI.
• AI evaluation and observability platforms: LangSmith, Weights & Biases, Arize AI, Helicone.
• Advanced AI concepts: agent architectures, multi-agent systems, context engineering, tool-use optimization, model evaluation pipelines, synthetic data generation, reinforcement learning from feedback, inference optimization.
• Vector databases, embedding systems, semantic search, knowledge graphs, event streaming platforms, data enrichment pipelines.
• Cloud platforms: AWS, Google Cloud, Microsoft Azure.

Bonus Qualifications

• Experience supporting enterprise customers in technical implementation or solutions engineering roles.
• Experience building AI-powered sales, marketing, or customer success automation systems.
• Familiarity with CRM platforms such as Salesforce or HubSpot.
• Experience with workflow automation tools: n8n, Zapier, Make.

What Makes Someone Successful in This Role

• Thinks like an engineer but understands business outcomes.
• Can rapidly prototype AI-driven solutions.
• Comfortable debugging complex workflow failures across multiple systems.
• Strong curiosity about emerging AI infrastructure and agent technologies.
• Able to communicate technical concepts clearly to both technical and non-technical stakeholders.
• Enjoys operating in fast-moving, ambiguous environments where experimentation is encouraged.