Senior Solutions Architect

Role Overview

• 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, not just a slide describing it.
• 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, continuously evolving your expertise as the landscape changes.
• Advocate for customers by synthesizing feedback and collaborating with Product and Engineering teams to shape future AI-related capabilities.

Requirements

• 4+ years in enterprise software, platform engineering, or solutions architecture, with a hands-on, consultative approach.
• You can write production-quality code in one or more modern languages (Python, Java, JavaScript/Node.js, Go, or similar) and can independently build and ship working integrations and prototypes in a customer's repository — not just architect them.
• 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.

Tech Stack

• AWS
• Azure
• Cloud
• Google Cloud Platform
• Java
• JavaScript
• Linux
• Node.js
• Python
• SDLC
• Go

Benefits

• Restricted Stock Units (RSUs)
• health, vision, and dental insurance
• mental health benefits