AI Full-Stack Engineer Jobs

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Design and evolve the agent runtime that manages reasoning, tool use, memory retrieval, and response generation. Build agent capabilities such as image generation, voice synthesis, video creation, web browsing, and code execution. Optimize large language model (LLM) integration through prompt engineering, context window management, multi-provider model routing, cost optimization, and latency reduction. Implement memory systems including long-term memory, working memory, episodic recall, and semantic search to enable agents to learn from interactions. Design autonomous behaviors including proactive actions, scheduled tasks, and goal-directed actions to make agents feel self-directed. Build evaluation and quality systems such as benchmarks, A/B testing, and metrics to assess agent behavior, personality consistency, and response quality. Experiment with new architectures like multi-agent collaboration, planning, and chain-of-thought reasoning. Collaborate with product and design teams to translate AI capabilities into intuitive user experiences.

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Build and ship internal tools quickly, focusing on improving hiring, finance, and operations workflows. Utilize LLMs, AI agents, and modern no-code/low-code tools to increase speed and efficiency. Develop tools that save time across the company. Write clean, maintainable code that integrates with existing APIs, databases, and third-party services and can scale reliably. Take full ownership of deployments from building, testing, shipping, to monitoring, ensuring reliability.

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Create functional black box tests for large codebases in various source languages. Create and manage Docker environments to ensure 100% reproducible builds and test execution across different platforms. Monitor code coverage and configure automated scoring criteria to meet industry benchmark-level standards. Leverage LLMs such as Roo Code and Claude to accelerate development cycles, automate repetitive tasks, and improve overall code quality.

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Create functional black box tests for large codebases in various source languages. Create and manage Docker environments to ensure 100% reproducible builds and test execution across different platforms. Monitor code coverage and configure automated scoring criteria to meet industry benchmark-level standards. Leverage LLMs such as Roo Code and Claude to accelerate development cycles, automate repetitive tasks, and improve overall code quality.

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Create functional black box tests for large codebases in various source languages; create and manage Docker environments to ensure 100% reproducible builds and test execution across different platforms; monitor code coverage and configure automated scoring criteria to meet industry benchmark-level standards; leverage large language models (LLMs) like Roo Code and Claude to accelerate development cycles, automate repetitive tasks, and improve overall code quality.

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Create functional black box tests for large codebases in various source languages. Create and manage Docker environments to ensure 100% reproducible builds and test execution across different platforms. Monitor code coverage and configure automated scoring criteria to meet industry benchmark-level standards. Leverage LLMs (Roo Code, Claude) to accelerate development cycles, automate repetitive tasks, and improve overall code quality.

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Create functional black box tests for large codebases in various source languages. Create and manage Docker environments to ensure 100% reproducible builds and test execution across different platforms. Monitor code coverage and configure automated scoring criteria to meet industry benchmark-level standards. Leverage LLMs (Roo Code, Claude) to accelerate development cycles, automate repetitive tasks, and improve overall code quality.

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Lead the deployment, performance, and reliability of AI agents operating in live, high-stakes healthcare environments. Architect and scale full-stack systems integrating with EHRs, legacy healthcare platforms, and real-time voice infrastructure. Drive technical strategy for customer-facing solutions, collaborating with product and engineering to translate client needs into scalable architecture. Mentor engineers and set standards for code quality, testing, security, and HIPAA-compliant development. Shape product roadmap by identifying systemic challenges in customer workflows and proposing high-leverage technical solutions.

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Design, build, and maintain full-stack applications powering identity and access management (IAM) experiences. Develop and integrate AI/ML models for identity use cases such as fraud detection, anomaly detection, risk-based authentication, and identity verification. Lead and execute SSO migrations across products and platforms, consolidating authentication flows while minimizing user disruption. Drive domain consolidation initiatives by unifying identity systems, services, and user data models across multiple platforms or brands. Improve developer experience by building internal tools, SDKs, APIs, and documentation that simplify identity integrations. Design and evolve secure, scalable APIs supporting authentication, authorization, and identity data services. Partner with Security, Platform, and Product teams to implement and standardize protocols and patterns such as OAuth 2.0, OpenID Connect, SAML, JWT, and zero-trust architectures. Ensure AI-powered identity systems are observable, explainable, and production-ready with robust monitoring and feedback loops. Balance security, performance, and usability while maintaining privacy and compliance. Contribute to architectural decisions, technical design discussions, and code quality standards.

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The role involves building the systems that power AI agents, working across the backend including data pipelines, integrations, and agent infrastructure. Responsibilities include contributing to projects like developing features for AI assistants (e.g., charts and alerts in Slack, natural language queries, managing platform resources), log visualization with filters and charts to monitor agent behavior, adding dynamic time-based knowledge that auto-updates from external sources, and implementing agent memory for conversation awareness and context retention. The engineer will work alongside senior engineers on larger initiatives and take ownership of smaller projects end-to-end as they ramp up, contributing to real problems from day one and progressively operating with greater independence within the codebase.