AI Specialist

Responsibilities

Expert-Level Solutions/Sales Engineering

• 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.

Collect and Propagate Product Feedback

• 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.

Scale the AgentControl Business

• 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.

Technical Leadership & Communication

• 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.

Qualifications

AI & Technical Expertise

• 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.

Mindset & Approach

• Strong but loosely-held opinions about AI—you have a point of view but update it based on evidence.
• Ability to anticipate where the AI landscape is heading and position products accordingly.
• Deep curiosity about how AI changes software development, with an obsession for staying current on new AI technology.
• Natural storyteller who can take new technology and craft compelling narratives that resonate with technical audiences.
• Thrive in ambiguity—you love figuring it out, building new processes, and working in undefined spaces.

Compensation

Target pay ranges based on Geographic Zones for Level 4:

• Zone 1 (San Francisco/Bay Area, NYC, Boston, Seattle): $214,800 - $295,350
• Zone 2 (Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago): $193,400 - $265,870
• Zone 3 (All other US locations): $182,600 - $251,020

Compensation includes Restricted Stock Units (RSUs), health, vision, dental insurance, and mental health benefits in addition to salary. Exact compensation may vary based on skills, experience, and location.