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Automation-first security engineer building integrations, tooling, and pipelines to make compliance, privacy, and security continuous at Mindtickle, using Python, GCP, and AI tools like Claude Code and MCP servers.
The Applied AI Engineer will build and maintain production-grade AI agents, machine learning models, and data-driven dashboards to support real-time decisioning and risk management. The role focuses on developing governed, auditable AI systems using Python, TypeScript, and SQL within a high-scale Web3 and iGaming environment.
About Understood Understood is a nonprofit focused on shaping the world for difference. We raise awareness of the challenges and strengths of people who learn and think differently. Our resources help people navigate…
About TubeScience Labs TubeScience Labs is the applied-AI team inside TubeScience — the largest performance-video company in paid social. TubeScience is Meta's largest creative partner and AppLovin's #1…
Builds and modernizes large-scale automotive retail platforms (AutoSync) using full-stack tech, cloud-native architectures, and AI-driven workflows to improve dealership operations, marketing, and sales.
This role involves building production-grade agentic systems and AI-ready data platforms for enterprise clients using Snowflake, dbt, Airflow, and LLM frameworks. The engineer will focus on unstructured data extraction, agent orchestration, and establishing evaluation practices for non-deterministic AI workflows.
The Data Engineer will build and maintain reliable ELT pipelines and data models within an Azure-based environment to support analytics and AI products. The role involves working in a cross-functional squad to ensure high-quality, governed data integration across the company's professional services subsidiaries.
The Senior QA Engineer will own functional and automated testing for applications, leveraging Playwright and AI-assisted tools to improve coverage and release readiness. This role involves building automation frameworks, mentoring team members, and integrating quality practices into CI/CD pipelines.
The Lead Program Manager will oversee the design, implementation, and operational launch of a large-scale Agentic AI platform for telecommunications networks. The role requires deep expertise in AI/ML, cloud-native technologies, and network operations to drive autonomous network transformation.
Senior Technical Program Manager driving AI-first content platform programs for Google Search, managing multi-quarter roadmaps, cross-organizational dependencies, and content lifecycle velocity across engineering and product teams.
Yext (NYSE: YEXT) is the enterprise agentic marketing platform. Built on the world's most comprehensive structured data platform for local businesses, Yext gives brands and their partners the visibility…
The Role You'll build the agent systems at the core of our product. These systems turn customer goals into reliable, multi-step execution across real tools and services. This is not about building demos. You'll…
AI DevOps Engineer designing, automating, and securing AWS cloud-native infrastructure while integrating AI-powered tools into CI/CD pipelines, observability, security, and infrastructure automation.
Data Engineer building scalable batch and streaming pipelines, data products, and AI-facing integration layers (e.g., MCP servers) for an internal Agentic AI ecosystem using Python, SQL, dbt, orchestration tools, and cloud data platforms.
Builds AI-enhanced full-stack applications by designing frontends, APIs, and data services while integrating AI tools and capabilities into enterprise solutions.
Roles & Responsibilities Develop, maintain and enhance Python-based applications and services. Design and implement scalable, reliable and reusable software components using Python and open-source frameworks.…
Design and build AI-driven automation and enterprise integrations to modernize IT workflows, using Python/Go/TypeScript and platforms like Slack, Okta, and Workday in New York City.
Build internal developer platforms and AI tooling frameworks at Braze, the customer engagement platform, using Ruby on Rails, Kubernetes, and Kafka to enable engineers to ship faster and safely deploy AI agents.
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