Lead AI Engineer- GTM Systems
New
S
SamsaraIoT, Connected Operations
This is a remote role open to candidates in the US, except for San Francisco and New York.Full-TimeLead
Salary$131,197.50 — $176,400 USD
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Job Details
- Experience
- 10+ years of software engineering experience, with a track record of building and shipping production-grade backend systems; 3 years of Technical Lead experience.
- Required Skills
- AWSNode.jsPythonSalesforceFastAPILangChain
Requirements
- Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience.
- 10+ years of software engineering experience with a track record of building production-grade backend systems.
- Minimum of 3 years of Technical Lead experience.
- Demonstrated experience personally building and deploying AI agents for end users.
- Hands-on proficiency with LLM orchestration and agentic frameworks such as LangGraph, LangChain, or CrewAI.
- Experience designing and implementing RAG systems, including vector databases and embedding pipelines.
- Strong backend engineering fundamentals in Python and/or Node.js, including FastAPI and async patterns.
- Proficiency with AWS cloud-native infrastructure (Bedrock, Lambda, SQS/SNS).
- Strong communication skills with experience presenting architectural visions to non-technical stakeholders.
Responsibilities
- Define and own the technical vision for AI-powered GTM systems, establishing architecture strategy for low-code automation and custom agentic builds.
- Create and publish reference architectures, design patterns, and decision frameworks for the engineering team.
- Lead architectural design for high-complexity systems, including multi-system integrations and real-time event processing.
- Evaluate, select, and drive adoption of emerging AI tools and platforms to maintain a competitive edge.
- Serve as the organization's technical authority on LLM orchestration, including prompt safety, RAG, and multi-agent coordination.
- Own integration architecture strategy, defining patterns, APIs, and data models across GTM systems.
- Partner with VP-level stakeholders to translate business goals into concrete architectural roadmaps.
- Conduct architecture reviews to provide feedback, identify risks, and improve system design quality.
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