Customer Engineer, AI

About LogicMonitor

At LogicMonitor, we value trust, customer obsession, agility, and a commitment to continuous improvement, which form the bedrock of our vibrant culture. We are dedicated to fostering a high-performance environment where employees are empowered to achieve their best and drive growth.

This role for a Customer Engineer, AI is open to candidates based in or near San Francisco, CA. LogicMonitor operates with 'Centers of Energy' – key locations designed for team connection, collaboration, and innovation. Discover more about life at LogicMonitor on our Careers Page.

LM Envision: Our AI-Powered Platform

LM Envision, LogicMonitor's leading hybrid observability platform, is powered by AI to provide modern enterprises with unparalleled operational visibility and predictability across their IT stacks. This ensures exceptional employee and customer experiences. AI and Machine Learning are deeply integrated into every aspect of LM Envision, helping IT teams boost efficiency, reduce alert fatigue, proactively predict trends, and accelerate enterprise growth and transformation.

Our customers appreciate LogicMonitor's ability to unify cloud and traditional IT views, evidenced by low churn rates and strong expansion. LogicMonitor holds the highest Net Promoter Score among IT Infrastructure Management providers and is a Great Place To Work® certified company, recognized as one of BuiltIn's Best Places to Work for seven consecutive years.

The Role: Customer Engineer, AI

We are seeking an Applied AI Engineer who will bridge product, AI engineering, and customer success. In this role, you will ensure AI capabilities are not just deployed, but also widely adopted, robust, and deliver significant value within customer environments. You will act as a crucial technical partner, both internally and externally, managing the entire loop from prototyping and metrics analysis to insights generation and roadmap feedback.

This is a unique opportunity, distinct from traditional support or operations. You will be responsible for building reliable systems, defining critical evaluation signals, influencing model and product behavior, and scaling AI adoption across our diverse customer base.

Key Responsibilities:

• Ensure customer success post-deployment: Drive adoption, measure value realization, and provide best practices to maximize the impact of AI capabilities.
• Act as technical owner: Serve as the primary technical advisor for customers, designing custom configurations, integrations, and prompt or agent workflows tailored to their specific environments.
• Prototype and evaluate: Build proofs-of-concept with customers, define robust evaluation metrics, conduct experiments, and analyze errors to enhance model and feature quality.
• Drive product improvements: Translate valuable customer feedback and production learnings into clear, actionable requests for our Product and Engineering teams.
• Instrument reliability and observability: Develop comprehensive health monitors, logging mechanisms, and drift detection to ensure stable and measurable AI performance in production.
• Resolve and automate: Investigate and troubleshoot production issues related to data, APIs, and model behavior, creating durable fixes and automation to prevent recurrences.
• Enable and educate: Lead engaging workshops, demos, and internal enablement sessions to build confidence and deep understanding of LM Envision's AI capabilities.
• Stay current: Continuously explore and apply emerging techniques in LLMs, generative AI, agent frameworks, and evaluation methods to advance the product's capabilities.

What You'll Need:

• 2-3 years of experience in a customer-facing technical role, such as solutions engineering, forward-deployed engineering, AI/ML ops, or applied research with deployment responsibilities.
• Strong solution architecture skills in designing enterprise software systems and AIOps systems.
• Hands-on experience with LLMs, generative AI, or agent frameworks, including prompting, retrieval, chaining, and evaluation.
• Proficiency in Python scripting for AI/LLM tooling and system observability/integration workflows (e.g., API debugging with Postman) is preferred.
• Ability to design effective evaluation metrics, perform thorough error analysis, and implement performance monitoring.
• Strong communication skills, capable of explaining complex AI ideas clearly to engineers, product teams, and non-technical stakeholders.
• Comfort working in ambiguous environments, adept at balancing trade-offs and managing multiple stakeholders.

Key Skills/Competency:

• AI Adoption
• Technical Advising
• Solution Architecture
• LLMs / Generative AI
• Python Scripting
• Evaluation Metrics
• Product Feedback
• System Observability
• Troubleshooting
• Customer Success