Senior Staff Engineer, Software Autonomy (R5125)
The Senior Staff Software Engineer, Autonomy functions as a hands-on technical lead and subject matter expert, collaborating with teammates and customers to build edge-AI and autonomy software for platforms across sea, air, and space. Responsibilities include working closely with customers to understand requirements, writing code, developing new capabilities, and ensuring successful software/hardware integration. The role involves mentoring teammates, designing tactical autonomy algorithms for unmanned aircraft to perform complex missions across various domains, developing high-performance software modules for planning, decision-making, and behavior execution in dynamic and adversarial environments, implementing and testing behavior architectures for multi-agent coordination and target engagement, and integrating hybrid autonomy approaches blending classical and learning-based methods. The engineer will collaborate with cross-functional teams to ensure seamless integration on real-world platforms, deploy capabilities to platforms, participate in field tests and flight demos, analyze mission data to diagnose failures and optimize models, contribute to R&D and autonomy roadmapping, support defense-focused programs and customer needs by adapting solutions, provide software handover and training to customers, and develop and maintain technical documentation. Travel is required for deployment, training, and flight testing, typically around 10-15% to different office locations and ~30% for customer site visits.
Legal Advisor (US Bar Admitted) - Freelance AI Trainer
Contributors may generate prompts that challenge AI, evaluate AI-generated solutions for correctness, assumptions, and logic, improve AI reasoning to align with first principles and accepted standards, and apply structured scoring criteria to assess multi-step problem solving.
Materials Engineer & Python Expert - Freelance AI Trainer
You design computational material science problems to challenge a frontier AI model with problems that have verifiable answers by code and require specialized tools like ObsPy, instaseis, pyrocko, MITgcm, flopy/MODFLOW, or others. You pick an anchor tool and design a problem focusing on its waveform-processing kernels, geophysical inversion routines, sub-surface flow solvers, or community-validated data pipelines. You write a Python reference solution, supply input files and model or domain definitions where necessary, decide the numerical answer and required tolerance, test the problem against the AI model in batches of parallel attempts, tune the problem difficulty to achieve a low pass rate, and submit the task to a senior reviewer for quality feedback. Calibration involves tuning the problem by rewriting scenarios, tightening parameters and solver tolerances, and observing the model's behavior, which builds deeper command of the tool and understanding of how the AI model navigates complex geophysical problems.
Mechanical Engineer & Python Expert - Freelance AI Trainer
Design computational engineering problems to challenge a frontier AI model, ensuring each problem has an answer verifiable by code and requires a specialized tool such as Cantera, CoolProp, CalculiX, OpenFAST, or others. Produce problems that run inside a sealed Linux container with the pre-installed tool and a programmatic judge that grades the model's answer. Select an anchor tool and design a problem focusing on its solvers, simulation kernels, or domain-specific models. Write Python reference solutions, supply input files and geometry or mechanism definitions as needed. Determine the numerical answer and set a domain-appropriate tolerance for correctness. Test and tune the problem against batches of parallel model attempts until the agent's success rate falls within the 10-30% range. Submit the completed task for senior reviewer feedback to ensure high task quality. Calibrate problems by rewriting thermodynamic cycles, adjusting material models and boundary conditions, and monitoring AI agent behaviors to refine problem difficulty. Acquire deeper command of the anchor tool and develop practical intuition for how the AI model handles complex thermal, structural, and fluid mechanics challenges.
Enterprise Account Executive
The AI Outcomes Manager will partner with executive sponsors and end users to identify high-impact use cases and turn them into measurable business outcomes on Glean. They will lead strategic reviews and advise customers on their AI roadmap to ensure maximum value from Glean's platform. Responsibilities include translating business needs into clear problem statements, success metrics, and practical AI solutions, collaborating with Product and R&D to shape priorities, conducting discovery workshops, scoping pilots, and guiding rollouts to drive breadth and depth of adoption of the Glean platform. The role involves designing and building AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability. Additionally, the AI Outcomes Manager will proactively identify expansion opportunities and drive engagement across teams and functions.
Senior Manager, Revenue Operations
The AI Outcomes Manager partners with executive sponsors and end users to identify high-impact use cases and turn them into measurable business outcomes on the Glean platform. They lead strategic reviews and advise customers on their AI roadmap to maximize value, translate business needs into clear problem statements, success metrics, and practical AI solutions while collaborating with Product and R&D. They conduct discovery workshops, scope pilots, guide rollouts to drive adoption of the Glean platform, design and build AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability, and proactively identify expansion opportunities and drive engagement across teams and functions.
Product Manager, AI Quality
Partner with executive sponsors and end users to identify high-impact use cases and turn them into measurable business outcomes on Glean. Lead strategic reviews and advise customers on their AI roadmap to ensure maximum value from Glean’s platform. Translate business needs into clear problem statements, success metrics, and practical AI solutions while collaborating with Product and R&D to shape priorities. Conduct discovery workshops, scope pilots, and guide rollouts to drive breadth and depth of adoption of the Glean platform. Design and build AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability. Proactively identify expansion opportunities and drive engagement across teams and functions.
Tech Lead Manager, Admin Console
The AI Outcomes Manager partners with executive sponsors and end users to identify high-impact use cases and turn them into measurable business outcomes on Glean. They lead strategic reviews and advise customers on their AI roadmap to maximize value from Glean’s platform. The role involves translating business needs into clear problem statements, success metrics, and practical AI solutions, collaborating with Product and R&D to shape priorities. Responsibilities include conducting discovery workshops, scoping pilots, guiding rollouts, and driving the breadth and depth of adoption of the Glean platform. The manager designs and builds AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability. They also proactively identify expansion opportunities and drive engagement across teams and functions.
Forward Deployed Engineer - Agents(Remote)
As a Forward Deployed Engineer - Agents, you will lead the end-to-end implementation of AI Virtual Agents and CX automation workflows for customers, owning the entire process from discovery and scoping through launch and optimization. Responsibilities include configuring agent workflows, decision logic, and automation behaviors to maximize accuracy, reliability, and business outcomes; implementing guardrails and validation frameworks to ensure safe, compliant, and predictable agent performance; building, testing, and validating integrations with enterprise systems such as CRM, ticketing, telephony, and data platforms; partnering with customer technical stakeholders to define success criteria, gather requirements, and deliver against timelines; translating customer needs into clear implementation plans and documentation; running tight feedback loops with Engineering and Product to improve platform capabilities; and collaborating with Product, Engineering, Design, and GTM teams to deliver repeatable, best-in-class deployments.
Software Engineer (Brazil)
Design, develop, test, deploy, maintain, and improve scalable, secure, and high-performance backend systems with a focus on high availability, low latency, and cost-effectiveness. Act as the subject matter expert in infrastructure when designing new products and introducing new technology to existing products. Collaborate closely with engineering and research teams to integrate infrastructure components with product features to optimize system performance and user experience. Design event-driven architectures and develop APIs and microservices for real-time processing and analytics. Ensure system reliability, performance, and scalability through monitoring, logging, and error handling. Stay current with emerging trends, technologies, and methodologies to enhance infrastructure capabilities. Participate in code reviews, contribute to open-source projects, and mentor junior engineers.
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