Trustero
Full-Stack AI Engineer
Job Description
About Trustero
Trustero is an advanced AI application, purpose-built for the Security and Compliance vertical. Our patented AI agents can accurately and consistently do the most time-consuming jobs in Governance, Risk, and Compliance, like perform gap analysis, provide remediation guidance, questionnaire automation, evidence collection + mapping, and more, saving companies hundreds-of-thousands of dollars and returning 100s of valuable working hours each month.
Role Overview
We are seeking a skilled Full Stack AI Engineer to join our in-person team in Palo Alto, California. As a Full Stack AI Engineer, you will be responsible for designing, developing, and maintaining applications using modern client frameworks (e.g React) and integrations with the latest LLM/RAG APIs and frameworks (e.g. OpenAI, Anthropic, Haystack).
Salary Range: $100,000 – $140,000 USD per year, plus stock options, based on experience and qualifications.
Salary Range: $150,000 – $250,000 per year
Key Responsibilities
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Develop and maintain responsive front-end applications using React.
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Build and enhance RESTful APIs to support a seamless user experience.
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Design and optimize SQL queries and database schemas for high performance and scalability.
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Collaborate with cross-functional teams to define, design, and ship new features.
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Translate vague requirements and designs into elegant, functional products.
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Write clean, maintainable, and testable code following best practices.
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Participate in code reviews and provide constructive feedback.
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Debug and resolve performance and reliability issues across the stack.
Requirements
Requirements
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3+ years of software engineering experience with a focus on Full Stack Engineer using AI or a similar role.
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Bachelor’s degree in Computer Science, Software Engineering, or a related field (advanced degrees are a plus).
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Proficiency in React, RESTful API design, and SQL database management.
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Proven success in delivering single-page applications (SPAs).
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Solid understanding of cloud platforms (AWS, GCP, or Azure) for production deployment and performance monitoring.
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Excellent collaboration and communication skills, able to work effectively with cross-functional engineering teams.
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Strong problem-solving abilities, adept at navigating complex technical challenges in a fast-paced environment.
Preferred Qualifications
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Proficiency in Golang, TypeScript, gRPC, and Protocol Buffers (Protobuf).
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Hands-on experience with LLM model APIs.
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Exposure to compliance, governance, or security-related platforms.
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Knowledge of microservices architecture, DevOps, and containerization tools (Docker, Kubernetes).