Design and build the systems behind the AI assistant, including agent flows, context retrieval, and data connections for Kubernetes infrastructure. Develop and maintain the public, permission-aware MCP server and cloud connectivity across AWS, GCP, and Azure.
You will own the end-to-end channel program strategy, including the recruitment and activation of GSIs, MSPs, and VARs to drive revenue. Additionally, you will manage and develop the Partner Account Manager team while maintaining strategic executive relationships.
You will be responsible for new logo acquisition across AMER enterprise accounts by building and running your own outbound pipeline. Additionally, you will manage the full enterprise sales cycle and develop the partner ecosystem for the Kimchi product.
Serve as a subject matter expert providing deep technical guidance and troubleshooting for customers using the Cast AI platform. Manage customer issues from intake to resolution while documenting best practices and mentoring junior team members.
You will design and build high-performance database gateway and agent services to automate database administration tasks. This involves developing recommendation engines for query improvements and ensuring data consistency and system reliability in production environments.
You will lead the commercial organization for the Kimchi product in the AMER region, owning revenue targets and forecasting. You will also recruit and manage a team of Enterprise Account Executives while driving outbound pipeline generation and executive-level deal sponsorship.
You will own the full sales cycle for enterprise accounts, driving outbound pipeline generation and identifying key contacts. You will lead value discovery conversations and demonstrate the platform's benefits to technical and business stakeholders to close deals.
Design, build, and operate backend services in Go while owning features end-to-end from implementation to production. Collaborate with cross-functional teams to debug complex issues and contribute to the product roadmap.
Design, build, and operate CI/CD pipelines and observability tooling to support internal engineering teams. Identify and resolve infrastructure bottlenecks to improve developer productivity and system reliability.
Design and build distributed systems to autonomously manage Kubernetes infrastructure at scale. Write production-grade Go services to interact with cloud provider APIs for real-time resource management.
Build and scale a partner and reseller ecosystem across EMEA North to drive revenue growth. Collaborate cross-functionally with sales, marketing, product, and legal teams to execute go-to-market strategies.
The Global Client Partner will manage 2-3 large enterprise accounts, focusing on driving revenue growth, upsells, and cross-sells. They are responsible for building executive-level relationships and managing the end-to-end commercial lifecycle, including contract negotiations and renewals.
You will provide technical expertise to sales teams to help clients understand product value and conduct compelling product demonstrations. Additionally, you will customize presentations, evaluate client technical needs, and represent the company at industry conferences.
You will own the end-to-end lifecycle of the routing model, including training, calibration, and release cadence. You will also build production-parity evaluation systems to ensure model performance and reliability in live traffic.
You will own the optimization of the inference stack to improve throughput, latency, and cost-efficiency. This involves tuning loaders, schedulers, and kernels while managing distributed inference topologies and quantization strategies.
You will lead hands-on demonstrations of inference products and configure Kimchi Studio workspaces within customer environments. Additionally, you will design and implement governance policies, including spending limits and model routing, while translating customer feedback into product improvements.
Design and build distributed systems that run agent fleets at scale across cloud and self-hosted environments with a focus on security. Ensure every agent action is observable, auditable, and governable while developing a remote-first experience for agent interaction.
You will architect planner, executor, and evaluator pipelines while managing agent memory and context across sessions. Additionally, you will own the harness surface, including TUI and MCP integrations, and work directly with users to resolve technical pain points.
You will own the inference API and associated infrastructure, ensuring reliability and scalability for AI services. Additionally, you will develop billing, usage metering, and role-based controls to support users ranging from solo developers to large enterprises.
Design and build distributed systems that autonomously manage Kubernetes infrastructure at scale across multiple cloud providers. Own features end-to-end, including design, implementation, testing, and production rollout of real-time cloud resource management services.
Design, build, and operate backend services in Go while owning features end-to-end from implementation to production. Debug complex production issues related to security, financial flows, and trust-critical infrastructure.
Design, build, and maintain CI/CD pipelines and observability tooling to streamline internal engineering workflows. Identify and resolve infrastructure bottlenecks to reduce friction for product teams and improve overall system reliability.
You will own features end-to-end, including design, implementation, testing, and production rollout. You will collaborate directly with product and engineering teams to solve complex problems in a fast-paced environment.
Identify and validate high-value customer problems, shape ambiguous opportunities into product direction, and lead products from discovery through 0-to-1 development, launch, adoption, and iteration. Partner with customers, engineering, design, and go-to-market teams; define success measures, make prioritization decisions, and communicate product decisions clearly.
You will provide technical expertise to guide sales teams and ensure clients understand the value of Cast AI products. Additionally, you will conduct product demonstrations, deliver tailored presentations, and represent the company at industry conferences.
Own a product area end-to-end by identifying customer problems and delivering impactful solutions through cross-functional collaboration. Drive market discovery and utilize AI tools to synthesize data, draft specifications, and track product metrics.
Lead and mentor a team of software engineers while spending at least half of the time contributing directly to product code. Own product development execution, ensuring the scalability and resilience of Kubernetes infrastructure across multiple cloud providers.
Design and execute data science experiments to develop and maintain state-of-the-art machine learning models for tabular and time-series data. Perform deep-dive data analysis to provide actionable business insights and collaborate with cross-functional teams to align projects with company goals.
The Sales Engineer will guide sales teams with technical expertise, conduct compelling product demonstrations, and customize persuasive presentations to ensure clients fully utilize the technology. Responsibilities also include evaluating client technical needs, proposing solutions, and representing the company at industry events.
