LaunchDarkly
Solution Engineer (AgentControl)
Remote Solutions Engineering role with clear candidate location fit.
PostedRecently added
Eligible countries1 accepted country
Seniority signalOpen level
Work settingRemote
Accepted candidate locations
USA
Role overview
Solution Engineer (AgentControl)
Requirements and responsibilities
Readable role content extracted into sections for faster review.
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:
- 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
Qualifications:
- 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
How This Role Connects
- You report through the AgentControl Specialist POD organization while maintaining a dotted-line relationship to the SE team.
- You collaborate closely with the AI Researcher, translating their strategic insights into customer-facing conversations and surfacing field intelligence that informs research priorities
- You coordinate with other AI SMEs across the SE organization to build collective expertise
How You'll Be Measured
- NNARR of AgentControl
- Activation - usage in terms of both volume (#AIC, #Evals) and breadth (#AI Experiments, #AI Guarded Releases)
- Quality of customer feedback integrated into product development
- Effectiveness of Solutions Engineering playbooks and documentation (# of enablement sessions / internal engagement (e.g. views), impact on conversion rate).
- Successful early-stage implementations and measurable customer impact
- Contribution to product-market fit through customer insights and technical validation
How You'll Be Measured
- Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, 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 - $251,0202*
How You'll Be Measured
- Improving the velocity and stability of software releases, without the fear of end customer outages
- Delivering targeted experiences by easily personalizing features to customer cohorts
- Maximizing the business impact of every feature through the ability to experiment and optimize
- Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types
- Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability
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