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Full-Stack AI Engineer

  • On-site
    • Palo Alto, California, United States
  • Engineering

Join Trustero to define how AI help security professionals. Make AI a productive part of every security practitioners’ daily lives. In-office Palo Alto, CA.

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 and developing AI first applications using modern client frameworks (e.g React), mid-tier RESTful APIs and back-end interactions with LLM/RAG APIs and frameworks (e.g. OpenAI, Anthropic, Haystack).

Salary Range: $150,000 - $220,000 USD per year, plus stock options, based on experience and qualifications.

Salary Range: $150,000 - $250,000 per year

Key Responsibilities

AI-First Feature Development

  • Design and implement agentic workflows using custom LLM prompts and tool call orchestration.

  • Integrate LLMs to drive product experiences, automate reasoning, and enhance decision-making.

  • Experiment with and refine LLM interactions, retrieval strategies (e.g. RAG), and context construction.

  • Evaluate LLM performance in production environments and iterate on prompts, toolchains, and logic flows.

Full Stack Engineering

  • Build and maintain scalable RESTful and gRPC APIs that serve AI-powered features and data pipelines.

  • Develop responsive and intuitive front-end interfaces in React that integrate seamlessly with AI capabilities.

  • Contribute across the mid-tier and backend stack, to support data processing, model integration, and business logic.

  • Translate abstract requirements into reliable, user-facing product features with minimal supervision.

Data & System Design

  • Design and optimize SQL queries and database schemas to support fast access to structured data.

  • Create and maintain vector stores and indexes to support retrieval-augmented generation.

  • Implement performant data pipelines for ingesting, chunking, and enriching documents used in AI workflows.

  • Ensure systems are designed with scalability, security, and observability in mind.

Collaboration & Quality

  • Work closely with cross-functional teams including product and design to ship impactful AI-powered features.

  • Participate in peer code reviews, mentor junior engineers, and contribute to shared best practices.

  • Maintain high standards for code quality, documentation, and test coverage across the stack.

  • Proactively identify and resolve technical challenges related to AI integration, performance, and maintainability.

Job requirements

Requirements

  • 5+ years of professional software engineering experience, with recent work in full stack or AI-focused roles.

  • Proficiency with modern full stack technologies, including React, RESTful APIs, and relational databases (e.g., PostgreSQL, MySQL).

  • Hands-on experience integrating LLMs and RAG systems via commercial or open-source APIs (e.g., OpenAI, LangChain, Cohere).

  • Strong grasp of deploying and monitoring production systems on cloud platforms such as AWS, GCP, or Azure.

  • Bachelor’s degree in Computer Science, Engineering, or a related field; advanced degrees are a plus.

  • Exceptional collaboration and communication skills; comfortable working across engineering, product, and design teams.

  • Proven problem-solving skills and ability to thrive in a fast-paced, ambiguous environment with evolving technical challenges.

Preferred Qualifications

  • Proficiency in Golang, Python, TypeScript, gRPC, and Protocol Buffers (Protobuf).

  • Exposure to compliance, governance, or security-related platforms.

  • Knowledge of microservices architecture, DevOps, and containerization tools (Docker, Kubernetes).

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