Key skills
PythonPyTorchTensorflowAILLMTensorFlowLangGraphDatabricks
About this role
Role Overview
- Represent the trustworthiness and confidence of serious expertise in practical AI applications in customer conversations (especially as an escalation point above an SE SME)
- Spearhead the early-stage implementation and adoption of LD4AI at scale, working closely with existing customers to ensure activation and churn prevention (alongside feedback)
- Develop and document Solutions Engineering playbooks and best practices that scale beyond our first customers
- Function as a tremendous partner to the LD4AI Chief of Staff, surfacing revenue-related insights with respect to the maturation of the product accordingly
- Support LD4AI POVs ran by on-the-ground SEs
- 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
- Confirm that LD4AI’s roadmap adheres to market demand and deliver exceptional user experiences, especially for the AI developer persona – vocalizing objections with data
- Deliver integrations against common, quantified customer requests in the form of code contributions, architecture diagrams, and whitepapers
- Function as a key technical asset in (with the Head of AI and the partnership team) technical partnerships with advantageous potential partners (like Anthropic, DataBricks, etc…)
- Publicly evangelize LD4AI at mainstream industry conferences, webinars, partner engagements, and strategic meetings
- Function as the primary owner of the disbursement of enablement material to the SE team, particularly to the designated by team/region SE LD4AI SMEs (for which you have partial, dotted-line accountability)
- Co-own Revenue Enablement of LD4AI along with the Head of AI and the LD4AI tetrad
- Work with the AI Researcher, the PMM team, and the Head of AI to build and maintain competitor playbooks
Requirements
- Minimum of 12 years of related technical experience
- Extensive experience with AI applications—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.
Tech Stack
- Python
- PyTorch
- Tensorflow
Benefits
- Restricted Stock Units (RSUs)
- Health insurance
- Vision insurance
- Dental insurance
- Mental health benefits