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Salary: USD 100,000 - 500,000 / annual
Tenstorrent is seeking an Applied AI Engineer to build and scale next-generation AI-powered solutions. This is a hands-on role at the intersection of AI, software, infrastructure, automation, and systems integration. You will identify opportunities to replace manual processes with AI and agentic solutions, then own those solutions from concept through implementation, integration, deployment, and iteration.
You will partner directly with teams across Operations, Customer Success, IT, Data Infrastructure, and AI Software to identify high-value internal workflows and deliver AI systems that scale across the organization. The role requires combining technical judgment, hands-on engineering, and a strong understanding of internal users' needs. Success is measured by reliable systems, sustained adoption, and data-driven improvements to the processes they support.
Tenstorrent is a leader in cutting-edge AI technology, having developed a high-performance RISC-V CPU from scratch. The company values collaboration, curiosity, and a commitment to solving hard problems. You will work in a fast-moving startup environment, taking significant ownership and navigating changing priorities.
Key responsibilities include:
- Designing, building, and deploying AI-enabled applications and software systems
- Translating ambiguous operational needs into technical requirements and practical AI/software solutions
- Integrating solutions into existing systems and debugging complex implementation issues
- Evaluating and operating AI systems in production, assessing quality and failure modes
- Developing reusable architectures and frameworks for agentic systems and AI-powered automation
- Monitoring production AI systems and using quality, reliability, and usage signals to guide iteration
Requirements:
- Bachelor's degree or higher in AI/ML Engineering, Computer Science, Computer Engineering, Electrical Engineering, or related technical field
- 5+ years of relevant technical experience
- Demonstrated experience designing, building, and deploying AI-enabled applications or software systems with hands-on contributions to code, architecture, evaluation, integration, and production readiness
- Strong technical understanding of software architecture, APIs, system integration, data pipelines, infrastructure, and distributed systems
- Hands-on experience with Python, SQL, Git, LLMs, AI/agentic frameworks, workflow automation, and AI coding agents/tools (Claude, Codex, Cursor, n8n, Rovo, or similar)
- Ability to translate ambiguous operational needs into technical requirements and practical solutions
- Experience evaluating and operating AI systems in production, including assessing quality and failure modes using representative data, evaluation methods, production signals, and human judgment
- Understanding of reliability, observability, security, privacy, data governance, performance, and cost considerations
- Ability to turn learnings into reusable architectures, tooling, documentation, or technical guidance
