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LaunchdarklyLaunchdarklyUnited States

Senior Solutions Architect

Solutions Architect focused on helping enterprise customers safely adopt and operationalize AI-powered applications and agentic workflows using LaunchDarkly's feature management platform. Build production integrations, reference implementations, and safe rollout patterns (progressive delivery, experimentation, guardrails) directly in customer codebases while acting as a trusted technical advisor.

145k – 235k
Remote4+ YOESolutions Architecture

About the role

Responsibilities

  • Lead complex Professional Services engagements focused on AI-enabled and traditional software delivery, aligning customer goals with LaunchDarkly best practices.
  • Partner with customers to design and build feature management into their LLM-powered applications, agentic workflows, and internal AI platforms.
  • Design and help implement safe rollout patterns for AI — progressive exposure, guardrails, kill switches, and prompt/model experimentation — directly in the customer's codebase.
  • Build reference implementations, integrations, and prototypes alongside customer engineers — writing production-quality code that demonstrates the pattern.
  • Work hands-on in customer environments to instrument AI systems with LaunchDarkly at inference-time and workflow-level decision points.
  • Support customers building and operating chatbots, copilots, and agent-based systems, helping them integrate LaunchDarkly into inference-time and workflow-level decisions.
  • Apply a consultative approach to understand customer architectures, gather detailed requirements, and influence key technical and organizational decisions.
  • Act as a trusted technical advisor to engineering, platform, DevOps, and AI leaders.
  • Identify and resolve technical obstacles that hinder value realization, particularly in complex, distributed, or AI-driven systems.
  • Establish yourself as a subject matter expert on LaunchDarkly and emerging AI delivery patterns.
  • Advocate for customers by synthesizing feedback and collaborating with Product and Engineering teams to shape future AI-related capabilities.

Qualifications

  • 4+ years in enterprise software, platform engineering, or solutions architecture, with a hands-on, consultative approach.
  • Ability to write production-quality code in one or more modern languages (Python, Java, JavaScript/Node.js, Go, or similar) and independently build and ship working integrations and prototypes in a customer's repository.
  • Hands-on experience with AI-assisted development tools (Claude Code, Cursor, or similar).
  • Understanding of Model Context Protocol (MCP) or similar tool-augmented/agent-based approaches, or strong interest in learning.
  • Ability to guide customers in DevOps, CI/CD, and modern release practices, including experimentation and progressive delivery.
  • Experience delivering across the full SDLC in enterprise environments and leading teams through development or platform transformations.
  • Strong grasp of how feature management and experimentation platforms accelerate and de-risk software delivery.
  • Hands-on experience with a major cloud provider (AWS, Azure, or GCP), Linux, and containers.
  • Open to 20% travel.

Nice-to-Haves

  • Passion for building the thing rather than just writing a deck.
  • Strong communication skills with experts from different backgrounds.
  • Desire to understand how systems actually work by getting into the code.
  • Self-starter with strong ownership and problem-solving mindset.

Compensation

Target pay ranges based on Geographic Zones for Level 4 (includes RSUs, health, vision, dental, and mental health benefits in addition to salary):

  • Zone 1 (San Francisco/Bay Area, NYC, Boston, Seattle): $171000 - $235400
  • Zone 2 (Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago): $154000 - $211000
  • Zone 3 (All other US locations): $145000 - $200000

Skills

Solutions ArchitecturePythonJavaJavaScriptNode.jsGoAWSAzureGCPLinuxContainersDevOpsCI/CDLLMsAi Governance
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