Resumo da vaga

Senior Solutions Architect

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

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, 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.

About You:

  • 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'd rather build the thing than write a deck about it — and you can do both.
  • You push back when the obvious answer is the wrong one, and you stay on a problem even when it's technically someone else's.
  • You can effectively communicate with experts from different backgrounds, and build strong stakeholder relationships.
  • You want to understand how systems actually work — the real version, not the marketing version — which usually means getting into the code.

Qualifications:

  • 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.

Qualifications:

  • Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $171,000 - $235,400**
  • Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $154,000 - $211,000**
  • Zone 3: All other US locations - $145,000 - $200,000**

About LaunchDarkly:

  • 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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