Senior Product Engineer
Lead development of advanced prompt engineering and retrieval pipelines by architecting and building scalable solutions that handle thousands of customer conversations daily across integrations like Zendesk, Intercom, and Salesforce, leveraging cutting-edge generation pipelines for rapid insights, accurate analysis, and meaningful customer interaction scoring. Architect real-time multimodal simulations by owning the development of realistic, interactive training experiences across voice, video, and chat using platforms like OpenAI, ElevenLabs, and Vapi, with simulations dynamically adapting to user input to create immersive learning environments. Drive high-performance user experiences by setting technical standards for intuitive, fast interfaces built with Next.js, ensuring UIs handle complex AI interactions seamlessly under demanding workloads, and mentoring other engineers to achieve the same technical standards. Shape technical decisions, own major parts of the product, mentor teammates, and push personal skills in full-stack development including frontend, backend, and AI integrations, making critical decisions about architecture, tooling, and product direction.
Software Engineer, Full Stack (Knowledge Innovation)
In this role, you will own the end-to-end development lifecycle for new platform capabilities and integrations with other systems, collaborate closely with engineers, data scientists, information systems architects, and internal customers to understand their problems and implement effective solutions, and work with product and research teams to share relevant feedback and iterate on applying their latest models.
AI Engineer (Partnerships)
The AI Engineer will craft and iterate on prompts that help AI agents reliably choose and use Firecrawl for web data tasks. They will build evaluation frameworks to test prompts across different models, use cases, and edge cases, iterating relentlessly based on results. The engineer will act as the technical partner contact in Slack channels, helping partners implement Firecrawl into their products and troubleshoot issues in real-time. They will obsessively test new models and evolving agent architectures to ensure Firecrawl's performance. The role includes creating integration guides and templates to simplify Firecrawl-powered feature deployment for partners, identifying new partnership opportunities by understanding AI tool usage of web data, and collaborating with Product and Engineering teams to surface partner feedback and shape the roadmap.
Head of Forward Deployed Engineering
As the Head of Forward Deployed Engineering at Lorikeet, you will build and lead a high-performing team of Forward Deployed AI Engineers who act as trusted technical partners to subscribers. You will develop the team’s expertise in Lorikeet’s AI platform and ensure they are equipped to lead implementation projects from kickoff through deployment and ramp up. You will coach the team to deeply understand customer workflows and business goals, configuring Lorikeet’s AI tools to drive meaningful outcomes and foster a culture of curiosity and proactive solutioning. Responsibilities include ensuring tight collaboration with the product team by capturing and communicating customer feedback and insights, supporting team members in navigating complex technical integrations, creating systems for ongoing skill development and operational excellence, and serving as an advocate to unblock the team and ensure they have the tools, clarity, and autonomy to build strong customer relationships. You will also be responsible for accelerating global hiring, technically ramping up new hires, and developing existing team members.
Software Engineer, Agent Studio
Work in small, autonomous teams oriented around customer problems. Contribute to the development of a simulation platform to test AI agents against real-world scenarios. Create intuitive, no-code content management tools to guide and test AI agents. Adapt traditional software development methodologies to accommodate AI agents' non-deterministic behavior, natural language interactions, and reliance on large language models. Accelerate generative agent creation using tools like Cursor and Claude Code and build self-improving systems based on real-world interactions, customer-driven feedback, and self-play.
Staff Context Engineer, AI Systems
As a Staff Context Engineer for AI Systems at MagicSchool, you will architect and optimize AI agents' reasoning, memory, and operation across complex educational workflows by designing context management systems that determine the information available to agents, maintaining state through multi-turn interactions, and dynamically retrieving knowledge efficiently without overwhelming attention budgets. Responsibilities include architecting adaptive context curation pipelines balancing comprehensiveness and token limits, inventing memory compaction and state management patterns for long-horizon tasks, designing evaluation pipelines for retrieval precision and reasoning coherence, building runtime data fetching systems for just-in-time knowledge retrieval, engineering token-efficient tool APIs and retrieval layers, collaborating cross-functionally with Product, Research, and Education teams to optimize context configurations, co-designing architectures with ML researchers and platform engineers, and mentoring engineers on context engineering principles and token budget awareness.
Staff AI Engineer, Graph DB
As a Staff AI Engineer specializing in RAG, Knowledge Graphs, and Memory Systems at MagicSchool, you will architect the information infrastructure powering the AI agents by designing and building systems for knowledge organization, retrieval, and memory that govern educational content access, curriculum relationships navigation, and coherent understanding in teaching workflows. You will architect and implement graph-based knowledge systems using databases such as Neo4j and Neptune to represent educational content relationships, develop and evolve ontologies and graph schemas for educational content, build GraphRAG systems combining graph traversal with vector similarity for content retrieval, and design sophisticated retrieval-augmented generation pipelines featuring hybrid search, multi-stage retrieval, and reranking. Additionally, you will design embedding and vectorization strategies, build document ingestion pipelines for structured and unstructured educational content, implement semantic parsing and extraction NLP pipelines, invent and operationalize long-horizon memory systems for session state and cross-conversation memory, and design evaluation frameworks to monitor retrieval and context performance. Cross-functional collaboration with product, research, educators, and ML teams to translate domain needs into technical architecture and to integrate knowledge graphs and vector stores with agent runtimes is expected. You will also mentor engineers on knowledge graph design, RAG architecture, embedding strategies, and retrieval optimization to enhance the team’s capabilities in knowledge-intensive AI systems.
Software Engineering Manager
Oversee the design and operation of the core platform including third-party providers, storage, billing, observability, security, and API. Provide technical leadership for various product and platform features. Improve developer experience to enable the entire team to ship faster. Guide efforts that bridge AI research to production across all modalities such as video, audio, image, and text. Understand the capabilities and limitations of state-of-the-art AI models and how to best leverage them in products. Partner with product, design, and research teams to ensure development is tightly aligned with user needs and business objectives.
Solutions Architect
The Solutions Architect partners with account executives to understand customer needs, prioritize high-impact use cases, and translate them into technical solutions. They design and deliver customer-specific demos and prototypes showcasing the models' capabilities, act as the primary technical advisor throughout the enterprise sales cycle from discovery to deployment, and develop and maintain technical pre-sales assets tailored for different audiences. They represent Reflection in customer meetings, partner summits, and industry events. Additionally, they lead the technical integration of Reflection's models within partner platforms, enable partner sales and solutions engineering teams through workshops and training, develop joint sales assets with partners, and provide technical expertise for priority partner accounts.
Freelance Software Developer (Ruby) / Quality Assurance (AI Trainer)
As an AI Tutor in Coding on the Mindrift platform, you will typically engage in code generation and code review, prompt evaluation, and complex data annotation. You will be involved in training and evaluation of large language models, benchmarking, and agent-based code execution in sandboxed environments. The role requires working across multiple programming languages including Python, JavaScript/TypeScript, Rust, and SQL. You will adapt guidelines for new domains and use cases and follow project-specific rubrics and requirements. Collaboration with project leads, solution engineers, and supply managers on complex or experimental projects is expected. Flexibility and quick adaptation to new requirements are essential.
Access all 4,256 remote & onsite AI jobs.
Frequently Asked Questions
Need help with something? Here are our most frequently asked questions.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.