GTM Engineer
Architect and scale the systems powering the revenue engine by designing scalable workflows and AI-powered automations. Manage data flows and integrations across the GTM stack to optimize prospecting and campaign orchestration.
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Architect and scale the systems powering the revenue engine by designing scalable workflows and AI-powered automations. Manage data flows and integrations across the GTM stack to optimize prospecting and campaign orchestration.
Collaborate with sales and success teams to design tailored technical solutions and manage the execution of product pilots. Act as a technical liaison between customers and the product team to influence the roadmap and ensure enterprise readiness.
Lead a team of web engineers to architect, implement, and optimize consumer-facing 3D web applications and high-performance architectures. Drive technical roadmaps, conduct code reviews, and coordinate with stakeholders to ensure scalable and maintainable software delivery.
Design and maintain scalable cloud infrastructure, deployment pipelines, and Kubernetes-based production environments. Collaborate with engineering and product teams to ensure reliability, security, and operational excellence through CI/CD and GitOps workflows.
Lead the design and implementation of complex, enterprise-grade multi-cloud and hybrid solutions for clients. Provide strategic guidance on cloud security, cost optimization, and the secure integration of enterprise AI capabilities.
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Lead the organization's migration from VMware to Red Hat OpenShift Virtualization and manage the full migration lifecycle. Responsible for the day-to-day operation, optimization, and maintenance of virtual machines on OpenShift.
Architect complex, cross-team technical solutions that align with business goals and ensure system scalability and security. Lead technical design for large-scale initiatives while mentoring engineers and evaluating emerging technologies to drive growth.
Review and improve real-world business scenarios used to train AI planning assistants in an educational context. Break down ambiguous problems, structure approaches, and deliver clear strategic recommendations.
Review and improve technical engineering scenarios used to train AI planning assistants in an educational context. Map decision trees and justify technical conclusions to ensure the AI can effectively tutor university-level students.
Create structured materials and reasoning to identify comparable companies for target businesses to train AI models. Review company characteristics and articulate the financial and strategic logic behind peer group selection.
Review and improve real-world marketing scenarios used to train AI planning assistants in an educational context. Break down campaign challenges, map decision trees, and justify strategic decisions with concrete data.
Review and improve real-world nutrition scenarios to train AI planning assistants in clinical and educational contexts. Break down dietary challenges, map decision trees, and justify clinical decisions with concrete data.
Review and improve real-world clinical scenarios to train AI planning assistants acting as nutrition tutors. Break down dietary challenges, map decision trees, and justify evidence-based reasoning for students and healthcare professionals.
The role involves rating, labeling, and ranking AI model outputs to improve the reasoning and language capabilities of LLMs. Responsibilities include creating prompts, generating training data, and rewriting text for clarity and adherence to guidelines.
The role involves rating AI model performance, labeling content, and creating training data to improve LLM reasoning and language capabilities. Responsibilities include generating prompts, rewriting text for clarity, and compiling diverse datasets for machine learning.
The role involves rating AI model performance, labeling data, and creating prompts to improve the reasoning and language capabilities of LLMs. Responsibilities also include generating training data through text transformation, summarization, and translation.
The specialist will rate AI model performance, label content, and create training data to improve LLM reasoning and language capabilities. Responsibilities include generating prompts, rewriting text for clarity, and compiling diverse datasets for model fine-tuning.
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The role involves rating AI model performance, labeling content, and creating prompts to train large language models. Responsibilities also include generating training data through text transformation, summarization, and translation.
The role involves rating AI model performance, labeling content, and creating training data through prompts and text transformations. Responsibilities also include rewriting text for clarity and converting audio or language content to improve LLM reasoning.
The role involves rating AI model performance, labeling content, and creating training data to improve LLM reasoning and language skills. Responsibilities include generating prompts, rewriting text for clarity, and compiling diverse datasets for model fine-tuning.
The role involves rating AI model performance, labeling content, and creating training data to improve LLM reasoning and language capabilities. Responsibilities include generating prompts, rewriting text for clarity, and compiling diverse datasets for model fine-tuning.
The role involves rating AI model performance, labeling content, and creating prompts to improve LLM reasoning and language capabilities. Responsibilities also include generating training data through text transformation, summarization, and translation.
The role involves rating AI model performance, labeling content, and creating training data to improve LLM reasoning and language capabilities. Responsibilities include generating prompts, rewriting text for clarity, and compiling diverse datasets for model fine-tuning.
The role involves rating AI model performance, labeling content, and creating training data through prompts and text transformations. Responsibilities also include rewriting text for clarity and converting audio or language to improve LLM reasoning and quality.
Design and build scalable ML data pipelines and translate R&D outputs into reusable libraries and products. Collaborate with customers and simulation engineers to embed AI models into practical engineering tools.
Design and implement robotics data capture solutions and technical pilots to help customers build Physical AI systems. Act as a technical partner to bridge the gap between customer requirements and the delivery of high-quality robotics datasets.
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Own the end-to-end development of internal tools, GTM data systems, and the web platform to automate manual business workflows. Partner with growth, sales, and RevOps teams to translate ambiguous business problems into scalable, reliable software primitives.
Design and implement collaboration solutions using Slack and its integration with the Salesforce ecosystem. Lead discovery sessions, configure workspaces, and execute user adoption and training strategies to optimize business productivity.
Design, develop, and maintain scalable backend services and microservice-based architectures using Java and GraphQL. Collaborate with cross-functional teams to implement AI-enabled features and provide technical leadership through mentoring junior engineers.
Design, develop, and maintain scalable backend services and microservice-based architectures using Java and GraphQL. Collaborate with cross-functional teams to implement AI-enabled features and provide technical leadership through mentoring junior engineers.
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