Applied AI Engineer

Hands-on, technical problem solver who enjoys using AI, software, automation, and systems integration to solve complex problems and build practical solutions.

High-agency and comfortable with ambiguity; able to ask the right questions, challenge assumptions constructively, make sound technical trade-offs, and drive progress with limited direction.

Strong systems thinker who understands how AI, software, infrastructure, data, APIs/MCP/Connectors, and workflows fit together and can turn ideas into reliable, scalable solutions.

Comfortable operating in fast-moving startup or scale-up environments, taking significant ownership, navigating changing priorities and learning quickly.

Clear, humble, and adaptable communicator who works collaboratively across engineering, partner teams, and leadership.

Bachelor’s degree or higher in AI/ML Engineering, Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, with 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, with hands-on experience in Python, SQL, Git, LLMs, AI/agentic frameworks, workflow automation, and AI coding agents/tools such as Claude, Codex, Cursor, n8n, Rovo, or similar.

Ability to translate ambiguous operational needs into technical requirements and practical AI/software solutions, integrate them into existing systems, and debug complex implementation issues by reproducing failures, testing hypotheses, and driving blockers to resolution.

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 reliability, observability, security, privacy, data governance, performance, and cost; and turning learnings into reusable architectures, tooling, documentation, or technical guidance.

How to turn repetitive, manual, and fragmented business processes into scaleable AI-forward products and automations.

How AI-native systems are selected, integrated, and deployed across complex hardware, software, infrastructure, and data environments.

How to monitor production AI systems and use quality, reliability, and usage signals to guide iteration.

How to develop reusable architectures and frameworks for agentic systems and AI-powered automation.

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.