AI Architect - GTM Systems

samsara; Stati Uniti; Remoto; USD 180.000 - 260.000; Tempo pieno

Descrizione del lavoro

Samsara is seeking a Lead AI Architect to shape the technical vision for AI-powered GTM automation across a large enterprise stack. The role combines architecture, hands-on prototyping, and cross-organizational influence spanning both low-code platforms and custom agentic systems.

You will define reference architectures, guide decisions on low-code versus custom code and synchronous versus event-driven flows, and lead high‑complexity integrations with Salesforce, NetSuite, and Marketo, including

Competenze

• 10+ years of software engineering shipping production-grade backend systems.
• Hands-on experience personally building and deploying AI agents used by real end users.
• Hands-on proficiency with LLM orchestration frameworks such as LangGraph, LangChain, CrewAI, or LlamaIndex.
• Experience designing RAG systems, vector databases, and embedding pipelines.
• Strong backend fundamentals in Python or Node.js, with async/event-driven architectures.
• AWS experience (Bedrock, Lambda/serverless, SQS/SNS/EventBridge) or equivalent.

Mansioni

• Define and own the technical vision for AI-powered GTM systems, including low-code automation and custom agentic builds.
• Create reference architectures and decision frameworks for when to use low-code vs custom code and synchronous vs event-driven flows.
• Lead architectural design for high-complexity GTM integrations across Salesforce, NetSuite, Marketo, and custom data stores.
• Evaluate and drive adoption of emerging AI tools and frameworks, assessing fit and risk without debt.
• Serve as the organization’s technical authority on LLM orchestration topics: prompt safety, RAG, model context management, and tool calling.

Descrizione del lavoro

Role overview

Lead AI Architect for go-to-market (GTM) systems, responsible for shaping the technical vision behind AI-powered automation across a large enterprise stack. This is a senior individual contributor role that combines architecture, hands-on prototyping, and cross-organizational influence — spanning both low-code platforms and custom-built agentic systems.

Responsibilities

• Define and own the technical vision for AI-powered GTM systems, covering low-code automation (Workato, MuleSoft, Salesforce Flow) and custom agentic builds using frameworks like LangGraph, LangChain, and MCP-enabled pipelines.
• Create reference architectures, design patterns, and decision frameworks that guide when teams should reach for low-code tools versus custom code, synchronous versus event-driven flows, and human-in-the-loop versus fully automated solutions.
• Lead architectural design for high-complexity GTM integrations across Salesforce, NetSuite, Marketo, and custom data stores, including real-time event processing and cross-platform orchestration.
• Evaluate and drive adoption of emerging AI tools and frameworks, assessing fit, risk, and maturity without accruing technical debt.
• Serve as the organization's technical authority on LLM orchestration topics: prompt safety, RAG systems, model context management, tool calling, and responsible AI design.

Requirements

• 10+ years of software engineering experience shipping production-grade backend systems, with at least 3 years in a Technical Lead capacity.
• Demonstrated experience personally building and deploying AI agents used by real end users.
• Hands-on proficiency with LLM orchestration frameworks such as LangGraph, LangChain, CrewAI, or LlamaIndex.
• Experience designing RAG systems, including vector databases, retrieval strategies, and embedding pipelines.
• Strong backend fundamentals in Python or Node.js, with experience in async and event-driven architectures.
• AWS experience (Bedrock, Lambda/serverless, SQS/SNS/EventBridge) or equivalent cloud-native infrastructure, plus strong communication skills for working with non-technical stakeholders.

Nice to have

• Familiarity with building evals and observability tooling for LLM systems (LangFuse, tracing, benchmark suites).
• Exposure to sales, deal desk, or finance workflows, including how leads progress through quote-to-renewal cycles.
• Experience with FastMCP, LiteLLM, or Model Context Protocol in production multi-agent systems.
• Familiarity with Salesforce as a data source, prompt engineering across providers, and full-stack development including custom applications and serverless programming.