Senior Cloud Native Developer

Description

We are looking for a Senior Cloud Native Developer to join our team in building an Enterprise Agent Development Platform — a production-grade, cloud-native ecosystem that enables engineering teams to define, orchestrate, deploy, and observe AI agents at scale. The platform standardizes agent development across the organization using LangGraph and Strands Agents on AWS AgentCore Runtime, providing a single-file developer experience where the platform handles runtime, tooling, observability, and deployment automatically. The initiative spans agent framework design, runtime architecture, marketplace integration, CI/CD automation, and enterprise-grade observability — reducing agent development from months to days while enforcing consistent security, quality, and governance standards. Responsibilities Define and implement enterprise-wide telemetry standards, monitoring architecture, and observability frameworks for AI agents, MCP servers, and runtime platforms Design and maintain OpenTelemetry-based instrumentation across agent frameworks and runtime environments Architect collector pipelines, processor configurations, and multi-exporter setups using AWS Distro for OpenTelemetry (ADOT) Build and optimize monitoring, alerting, and distributed tracing solutions using AWS CloudWatch and X-Ray at scale Implement enterprise-grade APM, custom dashboards, and NRQL-based alerting within New Relic Establish GenAI SIG semantic conventions for AI/LLM workloads and drive adoption across engineering teams Develop cross-runtime observability architectures to consolidate multi-vendor telemetry Instrument agent and LLM workflows using tools such as LangSmith or MLflow tracing Translate enterprise requirements into actionable engineering plans and provide technical leadership across observability initiatives Collaborate with platform, agent framework, and CI/CD teams to embed observability into the developer experience Requirements 3+ years of experience in observability or platform engineering with hands-on OpenTelemetry implementation Expertise in OpenTelemetry architecture, including SDK, Collector, and semantic conventions (including GenAI SIG conventions for AI workloads) Proficiency in AWS Distro for OpenTelemetry (ADOT), including collector pipeline design, processor configuration, and multi-exporter setup Skills in AWS CloudWatch (Logs Insights, EMF, composite alarms, cross-account aggregation) and X-Ray at scale (distributed tracing, service maps, trace groups, sampling rules) Background in New Relic in enterprise environments, including APM, custom dashboards, alerting, distributed tracing, and NRQL Knowledge of OpenTelemetry GenAI SIG semantic conventions or AI/LLM observability implementation Familiarity with agent/LLM observability tools such as LangSmith, MLflow tracing, or equivalents Understanding of cross-runtime observability architecture and multi-vendor telemetry consolidation patterns Proficiency in Python for ADOT instrumentation, SDK development, and integration with agent frameworks Capability to provide technical leadership and translate enterprise requirements into actionable engineering plans Excellent command of written and spoken English (B2+ level) Nice to have Experience in cross-team coordination on observability standards across multiple engineering teams Familiarity with AWS AgentCore Observability Background in Datadog or Dynatrace in hybrid environments Skills in Strands or LangGraph agent framework instrumentation

Requirements

• 3+ years of experience in observability or platform engineering with hands-on OpenTelemetry implementation

• Expertise in OpenTelemetry architecture, including SDK, Collector, and semantic conventions (including GenAI SIG conventions for AI workloads)

• Proficiency in AWS Distro for OpenTelemetry (ADOT), including collector pipeline design, processor configuration, and multi-exporter setup

• Skills in AWS CloudWatch (Logs Insights, EMF, composite alarms, cross-account aggregation) and X-Ray at scale (distributed tracing, service maps, trace groups, sampling rules)

• Background in New Relic in enterprise environments, including APM, custom dashboards, alerting, distributed tracing, and NRQL

• Knowledge of OpenTelemetry GenAI SIG semantic conventions or AI/LLM observability implementation

• Familiarity with agent/LLM observability tools such as LangSmith, MLflow tracing, or equivalents

• Understanding of cross-runtime observability architecture and multi-vendor telemetry consolidation patterns

• Proficiency in Python for ADOT instrumentation, SDK development, and integration with agent frameworks

• Capability to provide technical leadership and translate enterprise requirements into actionable engineering plans

• Excellent command of written and spoken English (B2+ level)

Responsibilities

• Define and implement enterprise-wide telemetry standards, monitoring architecture, and observability frameworks for AI agents, MCP servers, and runtime platforms

• Design and maintain OpenTelemetry-based instrumentation across agent frameworks and runtime environments

• Architect collector pipelines, processor configurations, and multi-exporter setups using AWS Distro for OpenTelemetry (ADOT)

• Build and optimize monitoring, alerting, and distributed tracing solutions using AWS CloudWatch and X-Ray at scale

• Implement enterprise-grade APM, custom dashboards, and NRQL-based alerting within New Relic

• Establish GenAI SIG semantic conventions for AI/LLM workloads and drive adoption across engineering teams

• Develop cross-runtime observability architectures to consolidate multi-vendor telemetry

• Instrument agent and LLM workflows using tools such as LangSmith or MLflow tracing

• Translate enterprise requirements into actionable engineering plans and provide technical leadership across observability initiatives

• Collaborate with platform, agent framework, and CI/CD teams to embed observability into the developer experience

Seniority

• Senior

Nice to have

• Experience in cross-team coordination on observability standards across multiple engineering teams

• Familiarity with AWS AgentCore Observability

• Background in Datadog or Dynatrace in hybrid environments

• Skills in Strands or LangGraph agent framework instrumentation