Key skills
PythonPyTorchTensorflowAILLMAnthropicTensorFlowLangGraphDatabricks
About this role
Role Overview
- Bring serious, credible expertise in practical AI applications to customer conversations.
- Spearhead the early-stage evaluation, implementation, and adoption of AgentControl at scale, working closely with existing customers to ensure activation and churn prevention (alongside feedback).
- Partner with the AI SME team to develop and document Solutions Engineering playbooks and best practices that scale beyond our early customers.
- Partner closely with the AI Strategy Lead and AI SME team surfacing revenue-related insights as the product is deployed.
- Lead AgentControl POVs to validate technical win and secure revenue from our largest customers.
- Collaborate extensively with product and engineering teams to ensure product concepts are technically feasible and align with LaunchDarkly's strategic goals.
- Drive continuous improvement by monitoring product performance, user experience, and market response, iterating based on actionable data and insights.
- Ensure AgentControl's roadmap tracks market demand and delivers an exceptional experience for the AI developer persona.
- Deliver integrations against common, quantified customer requests in the form of code contributions, architecture diagrams, and whitepapers
- Function as a key technical asset in technical partnerships with advantageous potential partners (like Anthropic, DataBricks, etc…)
- Publicly evangelize AgentControl at mainstream industry conferences, webinars, partner engagements, and strategic meetings.
- Partner with LaunchDarkly’s AI SE SME team to support broader organization enablement on AI and the AgentControl product.
- Support Field Team Enablement of AgentControl.
- Work with the AI Researcher, the PMM team, and the AI Strategy Lead to build and maintain competitor playbooks.
Requirements
- Extensive experience with AI applications including building, implementing, or selling AI solutions at scale
- Experience building multi-agent systems using frameworks like LangGraph, AgentBuilder, or AgentCore
- Hands-on experience evaluating AI agent performance at scale using automated evaluation methods
- Deep understanding of LLM mechanics (you've read 'Attention is All You Need' and can explain transformer architecture in detail)
- Experience building or interfacing with MCP (Model Context Protocol) servers
- Strong Python skills with experience building in PyTorch or TensorFlow
- Strong foundation in software engineering principles and current market trends
- Typically requires a minimum of 12 years of related experience.
Tech Stack
- Python
- PyTorch
- Tensorflow
Benefits
- Restricted Stock Units (RSUs)
- Health, vision, and dental insurance
- Mental health benefits