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