Observability Engineer – Telemetry Extension & ADOT Pipeline

We are looking for an Observability Engineer – Telemetry Extension & ADOT Pipeline to build and extend telemetry capabilities for enterprise AI and cloud-native platforms. In this role, you will focus on designing scalable observability pipelines, extending OpenTelemetry instrumentation, and developing reusable telemetry components that provide actionable insights into distributed systems. You will work closely with platform, AI, and DevOps teams to create flexible, configurable telemetry solutions that support performance monitoring, troubleshooting, and operational excellence at scale.

Our customer is a multinational corporation with more than a century of history and offices in over 180 countries. Their most ambitious goal at the time is to introduce a range of Reduced-Risk Products (RRPs). The target audience is more than 1 billion consumers around the globe. IT platform hosts 700+ applications.
Intellia’s mission is to help the client with the engineering of a comprehensive software ecosystem for a game-changing IoT product on the margin of innovative consumer experience and cutting-edge technology. Our teams are involved in the engineering of core platform components for best-in-class eCommerce, Digital Marketing and IoT solutions. As an Engineer, you will become a part of Core Architecture Team and be responsible for the architecture, implementation of best practices in our Digital Engineering Enterprise Platform.
The Platform is a set of services and internet applications that accelerate the development and delivery of software applications by taking care of common SDLC challenges. The Platform provides access and consumption for engineering teams to a set of services, technologies, practices for their development and for operating their application, ensuring a set of compliance and best practices.

• Design and implement observability solutions for AI platforms, agent-based systems, and distributed cloud-native applications.
• Instrument Python services using OpenTelemetry SDK and AWS Distro for OpenTelemetry (ADOT).
• Develop and maintain distributed tracing solutions using AWS X-Ray and OpenTelemetry.
• Configure telemetry collection, propagation, and export pipelines across AWS environments.
• Implement and maintain CloudWatch dashboards, metrics, logs, and alerting strategies for operational visibility and troubleshooting.
• Establish monitoring standards for AI agents, tool invocations, workflow execution, and service-to-service communication.
• Integrate observability capabilities with AWS AgentCore Observability and related platform services.
• Ensure proper W3C Trace Context and Baggage propagation across applications, APIs, and agent workflows.
• Instrument LangChain-based applications and AI services to capture traces, metrics, and execution insights.
• Partner with AI engineers and platform teams to identify performance bottlenecks, reliability issues, and optimization opportunities.
• Build structured logging and telemetry standards that support debugging, root-cause analysis, and operational governance.
• Contribute to observability best practices, platform standards, and engineering guidelines for AI and cloud-native systems.

• AWS Distro for OpenTelemetry (ADOT) collector configuration (pipelines, processors, exporters)
• OpenTelemetry SDK extension patterns (custom metrics, custom spans, configurable telemetry)
• Python SDK library design
• AWS CloudWatch Metrics and X-Ray export pipelines
• YAML-driven telemetry configuration schemas

• 4+ years of observability or platform engineering
• ADOT or OTel collector pipeline design
• Python SDK or library development

• Strands or LangGraph framework familiarity
• Customer-facing SDK extensibility patterns
• CloudWatch custom metrics and dimensions