Solutions Engineer

Ano Sys is an AI observability company building the monitoring and analytics platform for the agentic AI era. Our platform gives engineering teams end-to-end visibility into AI agents, LLMpipelines, and ML-powered applications — from user interaction through model inference to downstream business outcomes. We help organizations detect silent regressions, trace non-deterministic behavior,and turn massive telemetry streams into actionable insights, all in real time.

Backed by leading investors and built by a team of infrastructure and AI veterans, Ano Sys is defining the category ofAI-native observability.

We're a small, high-impact team, and every person here shapes the product, the culture, and the trajectory of the company. We look for intellectually curious individuals who combine critical thinking with meticulous attention to detail — people who can identify problems early, reason through ambiguity, and solve challenges independently
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If you thrive in fast-paced, high-ownership environments — where your work directly shapes a category-defining product — we'd love to hear from you.

As a Solutions Engineer at Ano Sys, you will serve as the primary technical interface between our platform and the engineering organizations evaluating and adopting it. You will work directly with engineering leaders, platform teams, and individual contributors at companies deploying AIagents, LLM-powered applications, and ML pipelines in production.

This role sits at the intersection of deep technical expertise and customer empathy.

You'll design end-to-end observability architectures, integrate our SDKs across diverse technology stacks, and translate complex production challenges into platform capabilities. You will also play acritical role in shaping the product roadmap by channeling firsthand customer insights back to our engineering and product teams.

The ideal candidate has a strong background in infrastructure, observability, or developer tooling and is comfortable operating across pre-sales, onboarding, and post-deployment workflows. You should be equally at home whiteboarding a distributed tracing architecture with a VP of Engineering and debugging an Open Telemetry integration with a senior developer.

• Partner with prospective and existing customers to deeply understand their observabilityrequirements for AI agents, LLM pipelines, and ML-powered applications in production environments
• Design, architect, and implement proof-of-concept integrations tailored to each customer'stechnology stack, deployment model, and organizational needs
• Deliver compelling technical demonstrations and architecture workshops that clearly articulate howAnoSys's platform addresses real-world production monitoring challenges
• Serve as the voice of the customer internally — collaborating with Product and Engineering to translate field learnings into roadmap priorities and feature specifications
• Build and maintain a library of technical documentation, integration guides, reference architectures, and best-practice resources that accelerate customer onboarding
• Provide technical guidance during the sales process, including RFP responses, security reviews, and technical due diligence sessions
• Develop reusable tooling, scripts, and automation that streamline common integration patterns acrossthe customer base

• 3+ years in a solutions engineering, sales engineering, or technical consulting role — preferably atan infrastructure, observability, or developer-tools company (e.g., Datadog, New Relic, Splunk,Grafana Labs, Honeycomb)
• Strong proficiency in Python and hands-on familiarity with cloud-native architectures across AWS,GCP, or Azure — including containerized and serverless environments
• Direct experience with observability and monitoring platforms, distributed tracing systems, orOpenTelemetry-based instrumentation in production settings
• Familiarity with AI/ML development workflows — including model serving, inference pipelines, prompt engineering, and agent orchestration frameworks (e.g., Lang Chain, CrewAI, OpenAI Agents)
• Excellent communication and presentation skills — you can lead an architecture review with a CTO,pair-program with a staff engineer, and present to a non-technical executive in the same day
• A self-directed, entrepreneurial mindset with the ability to manage multiple customer engagements simultaneously while maintaining a high bar for technical depth and quality
• Intellectual curiosity and a genuine passion for understanding how AI/ML systems behave — and fail —in production

• Experience building or contributing to developer SDKs, CLIs, or API client libraries
• Familiarity with data pipeline tools such as Apache Kafka, Google Pub/Sub, or Apache Beam
• Prior experience in an early-stage startup environment where you wore multiple hats and helped define processes from scratch
• Background in technical writing or developer advocacy