Solutions Architect, AI

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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 implement feature management strategies for AI systems, including LLM-powered applications, agentic workflows, and internal AI platforms.
Advise customers on safe rollout patterns for AI, such as progressive exposure, guardrails, kill switches, and experimentation for model behavior and prompts.
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.

You are a self‐starter and excited to take on hard problems.
You are passionate about helping customers and have a strong sense of ownership.
You can effectively communicate with experts from different backgrounds, and build strong stakeholder relationships.
You have a technical background and are interested in a customer-facing role.
You are a deeply curious individual, who is not comfortable with just getting enough context to give an answer. You feel the need to understand how things work underneath.

5+ years of experience in enterprise software, platform engineering, or solutions architecture roles.
Strong hands-on technical background with a consultative, customer-focused approach.
Experience implementing and advising across the full software development lifecycle in enterprise environments.
Proficiency in one or more modern programming languages, including Python, Java, JavaScript/Node.js, Go, or similar.
Experience working with low code/no code solutions i.e. Claude Code, Cursor, Retool etc
Experience working with AI/ML-enabled systems, such as:
Large Language Models (LLMs)
Prompt-driven or agentic workflows
Chatbots, copilots, or conversational interfaces
Model or prompt experimentation and evaluation
Familiarity with AI development tooling and datasets, including Python-based data workflows.
Understanding of Model Context Protocol (MCP) or similar approaches to tool-augmented or agent-based AI systems (or strong interest in learning).
Ability to guide customers in DevOps, CI/CD, and modern release practices, including experimentation and progressive delivery.
Experience leading teams through development or platform transformations.
Ability to synthesize large amounts of information and provide prescriptive technical recommendations.
Proven ability to manage multiple concurrent engagements while prioritizing effectively.
Experience in both pre-sales and post-sales customer engagements.
Experience with LaunchDarkly or other feature management / experimentation platforms.

Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $187,000 - $257,000**
Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $168,000 - $231,000**
Zone 3: All other US locations - $158,000 - $218,000**

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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