• Set the multi-year technical strategy for AI platform development, partnering with senior EPD leadership on long-term vision • Architect foundational AI systems that serve multiple product teams, including LLM orchestration frameworks, MCP infrastructure, and agent patterns • Own technical decisions with organization-wide impact where the right answer is ambiguous or contested • Define engineering-wide quality standards and best practices for AI development, establishing patterns that scale across teams • Drive technical alignment across the Agentic SDK team and product teams consuming AI capabilities • Invest deeply in coaching P4 engineers, helping them develop toward staff-level scope and strategic thinking • Represent CaptivateIQ's technical perspective in industry discussions, open-source contributions, or technical publications

• Design and implement AI-powered features end-to-end, from React frontends through Python services to LLM integrations • Build and maintain components of our Agentic SDK, enabling other engineering teams to leverage AI capabilities • Develop LLM orchestration workflows, including prompt engineering, tool calling, and agent design patterns • Implement MCP integrations and knowledge systems, connecting LLMs to tools, databases, and external services • Partner with product teams to translate requirements into technical solutions, delivering quarterly milestones on time with high quality • Contribute to technical design discussions and code reviews, helping establish best practices for AI development • Participate in team culture and hiring, including conducting interviews for engineering candidates

Rockstar is recruiting for a founding AI/ML engineer to join a dynamic team building the future of DevOps for the AI age. Our client is a well-funded, fast-growing startup backed by top-tier investors like Y Combinator and 8VC. Their mission is to help organizations gain insights and visibility into their complex systems and applications through a cutting-edge, AI-based observability platform that processes data at a massive scale. About the role They are looking for a talented and experienced AI/ML founding engineer to join the Middleware team. The candidate will play a key role in building AI on their observability platform to detect and fix issues automatically. In this role, the candidate will be able to design, develop, and deploy intelligent solutions that take action where their platform identifies problems. They are looking for someone to help them invent the future of DevOps for the AI age. Key Responsibilities: - Build AI-Powered Remediation Systems: Design and implement machine learning models that can identify, diagnose, and automatically resolve system issues detected by the observability platform. - Own the AI/ML Pipeline: Take end-to-end ownership of the AI lifecycle — from data collection and preprocessing to model training, evaluation, and deployment. - Integrate with Observability Stack: Work closely with the core platform team to integrate AI solutions into the existing observability infrastructure (e.g., logs, metrics, traces). - Experiment and Iterate: Rapidly prototype and experiment with different models and approaches (e.g., anomaly detection, root cause analysis, LLM-based insights) to find what works best. - Collaborate Cross-Functionally: Partner with product, backend, and DevOps teams to align AI capabilities with user needs and infrastructure realities. - Set the Technical Direction: As an early technical hire, contribute to foundational architecture decisions and establish best practices for AI/ML within the company. - Ensure Reliability and Scalability: Build systems that perform reliably at scale and integrate safely into production environments. - Stay Ahead of the Curve: Keep up with the latest advancements in AI/ML and observability to help shape the product roadmap. Qualifications: - Engineers with experience building AI products (do side-projects count?) - Solid software engineering skills: Proficiency in Python and TypeScript. - Systems knowledge: Understanding of observability tools (e.g., Prometheus, OpenTelemetry). - Owner mindset: Comfortable working in a fast-paced, ambiguous environment with limited structure and high ownership. Few more facts: - They are backed by some of the best investors in the world, like Y Combinator, 8VC, Fin Capital, Tokyo Black (Looker founder fund), Guillermo Rauch (founder of Vercel) and many more. - The candidate will grow fast and work at scale - they collect and process 1 petabyte of data monthly. So the candidate will be working with a large dataset to process and store. - The candidate likes being rewarded directly for high output. - The Founder and CEO built the company before, took it to 200 people, and raised $57m in venture funding. If the candidate is excited about the prospect of building an AI-based cutting-edge observability platform and working with a team of talented and passionate engineers, they are encouraged to apply for this position. Please include your GitHub.

Rockstar is recruiting for a founding AI/ML engineer to join a dynamic team building the future of DevOps for the AI age. Our client is a well-funded, fast-growing startup backed by top-tier investors like Y Combinator and 8VC. Their mission is to help organizations gain insights and visibility into their complex systems and applications through a cutting-edge, AI-based observability platform that processes data at a massive scale. About the role They are looking for a talented and experienced AI/ML founding engineer to join the Middleware team. The candidate will play a key role in building AI on their observability platform to detect and fix issues automatically. In this role, the candidate will be able to design, develop, and deploy intelligent solutions that take action where their platform identifies problems. They are looking for someone to help them invent the future of DevOps for the AI age. Key Responsibilities: - Build AI-Powered Remediation Systems: Design and implement machine learning models that can identify, diagnose, and automatically resolve system issues detected by the observability platform. - Own the AI/ML Pipeline: Take end-to-end ownership of the AI lifecycle — from data collection and preprocessing to model training, evaluation, and deployment. - Integrate with Observability Stack: Work closely with the core platform team to integrate AI solutions into the existing observability infrastructure (e.g., logs, metrics, traces). - Experiment and Iterate: Rapidly prototype and experiment with different models and approaches (e.g., anomaly detection, root cause analysis, LLM-based insights) to find what works best. - Collaborate Cross-Functionally: Partner with product, backend, and DevOps teams to align AI capabilities with user needs and infrastructure realities. - Set the Technical Direction: As an early technical hire, contribute to foundational architecture decisions and establish best practices for AI/ML within the company. - Ensure Reliability and Scalability: Build systems that perform reliably at scale and integrate safely into production environments. - Stay Ahead of the Curve: Keep up with the latest advancements in AI/ML and observability to help shape the product roadmap. Qualifications: - Engineers with experience building AI products (do side-projects count?) - Solid software engineering skills: Proficiency in Python and TypeScript. - Systems knowledge: Understanding of observability tools (e.g., Prometheus, OpenTelemetry). - Owner mindset: Comfortable working in a fast-paced, ambiguous environment with limited structure and high ownership. Few more facts: - They are backed by some of the best investors in the world, like Y Combinator, 8VC, Fin Capital, Tokyo Black (Looker founder fund), Guillermo Rauch (founder of Vercel) and many more. - The candidate will grow fast and work at scale - they collect and process 1 petabyte of data monthly. So the candidate will be working with a large dataset to process and store. - The candidate likes being rewarded directly for high output. - The Founder and CEO built the company before, took it to 200 people, and raised $57m in venture funding. If the candidate is excited about the prospect of building an AI-based cutting-edge observability platform and working with a team of talented and passionate engineers, they are encouraged to apply for this position. Please include your GitHub.