• Own product features end-to-end, from problem definition and architecture to deployment, monitoring, and continuous improvement • Build AI-driven product experiences and integrate modern AI tools into the engineering workflow • Collaborate cross-functionally with product, design, engineering, and business stakeholders to deliver impactful solutions • Contribute across the stack, including frontend, backend, APIs, integrations, and cloud-based services • Represent the company in technical and commercial discussions with clients, partners, and stakeholders • Drive technical discovery sessions, solution design, and architecture discussions • Mentor and upskill engineering teams on AI-assisted development practices and modern engineering workflows • Optimize applications for performance, scalability, maintainability, and user experience • Write clean, maintainable, well-tested, and well-documented code • Stay up to date with emerging technologies, AI trends, and modern software engineering practices

• Manage and grow the DOS and Training products and services • Assess & analyze the market & competitive landscapes and ensure VoC is captured in the product development lifecycle • Lead product strategies and roadmaps to grow WEC market share • Lead development of product heatmaps and guide demand creation priorities • Support account, sales & tendering teams to develop leads and opportunities • Support BUs, account, and sales teams (including OPx teams) to develop sales talking points and presentations • Oversee the product lifecycle management and support new product introduction (NPI) projects to meet business case goals • Support delivery P&L to establish tendering processes and tools • Be a consultant to tendering team for technical clarification, product pricing strategy, and WEC value proposition with customer • Work directly with customers for demand creation in coordination with other teams • Collaborate across the OPx organizations to align and lead consistent priorities • Support Sales Pacing preparation with OPx Regional Centers, Global Markets & BU Sales to report OE metrics, risks, and opportunities • Support software product development life cycle development, maintenance, and innovation

• Build agents that investigate incidents. They surface anomalies, answer "why is production broken?", and use ClickStack as their substrate. • Write skills, not just prompts. Build a library of reusable skills that captures how our team debugs, finds root causes, writes ClickHouse queries, and runs incident response, so agents pick up the right playbook instead of starting from scratch. • Own the agent stack end-to-end. Context engineering, tool design, evals, tracing, cost. You're responsible for whether the agent works in production. • Make ClickStack a great place to run AI workloads. Build the MCP servers, SDKs, and integrations that let customers' agents read telemetry, take action, and stay observable themselves. • Work in the open. Collaborate with OSS contributors and customers, debug their problems alongside them, and feed what you learn back into the product. • Tackle the hard parts. Latency, cost, context window limits, eval coverage, hallucinations on real telemetry.

• Build agents that investigate incidents. They surface anomalies, answer "why is production broken?", and use ClickStack as their substrate. • Write skills, not just prompts. Build a library of reusable skills that captures how our team debugs, finds root causes, writes ClickHouse queries, and runs incident response, so agents pick up the right playbook instead of starting from scratch. • Own the agent stack end-to-end. Context engineering, tool design, evals, tracing, cost. You're responsible for whether the agent works in production. • Make ClickStack a great place to run AI workloads. Build the MCP servers, SDKs, and integrations that let customers' agents read telemetry, take action, and stay observable themselves. • Work in the open. Collaborate with OSS contributors and customers, debug their problems alongside them, and feed what you learn back into the product. • Tackle the hard parts. Latency, cost, context window limits, eval coverage, hallucinations on real telemetry.