Lead Architect

Capital Group•Los Angeles, CA

9d•$201,683 - $322,693•Hybrid

About The Position

At Capital Group, you will operate at the center of enterprise architecture, defining the observability control plane that underpins modern distributed systems, multi-cloud platforms, and AI-driven workloads. As the firm’s technology landscape evolves, this role ensures observability capabilities scale to provide comprehensive visibility across applications, platforms, and AI-driven workloads. As a Lead Data Architect for Enterprise Observability, you will design and govern the end-to-end telemetry ecosystem—establishing how signals are generated, normalized, routed, and transformed into actionable intelligence across the firm. You will own the architecture and standards of this observability ecosystem while driving adoption across platform, application, and security teams. This role is responsible for defining the target-state observability architecture, including standardized telemetry schemas, OpenTelemetry-based pipelines, and a unified signal model spanning logs, metrics, traces, events, and AI-specific telemetry. You will architect end-to-end telemetry flows—from instrumentation at the application and platform layers through collection, enrichment, routing, and persistence—ensuring scalability, data integrity, and cost-efficient lifecycle management, and enabling a centralized observability control plane for the enterprise. You will also extend observability into the emerging AI domain, where traditional monitoring is insufficient. This includes defining architectures that capture AI-specific signals such as model performance, token usage, agent execution traces, and guardrail outcomes—providing visibility into correctness, safety, and cost characteristics not addressed by traditional monitoring approaches and enabling visibility into failure modes that are otherwise invisible to conventional systems. As a senior individual contributor, you will drive cross-layer architectural cohesion, aligning infrastructure, platform, application, and business observability into a unified model across the enterprise. You will establish patterns for service-level indicators and objectives, distributed tracing as a primary debugging primitive, and intelligent telemetry pipelines that support AIOps capabilities such as anomaly detection, signal correlation, and automated response—enabling faster detection, diagnosis, and resolution of issues across systems and workloads. This is a hands-on architecture role where you will translate strategy into executable designs—defining standards, reference architectures, and implementation patterns while driving adoption across engineering teams to ensure consistency and scale. You will act as a technical authority, influencing platform direction, resolving complex design tradeoffs, and ensuring observability is embedded as a foundational capability for resilience, governance, and intelligent operations at scale.

Requirements

10+ years of experience in software, platform, or enterprise architecture roles.
5+ years of experience focused on observability, monitoring, or operational platforms in cloud environments.
Deep understanding of distributed systems observability (tracing, metrics at scale, and log aggregation).
Strong knowledge of OpenTelemetry concepts and telemetry pipelines.
Working knowledge of AIOps concepts, including anomaly detection, alert correlation, and time-series analysis.
Experience designing scalable, resilient, and cost-efficient cloud architectures (AWS preferred).
Strong collaboration and influence skills across engineering organizations.

Nice To Haves

Experience with AI/LLM observability.
Experience with security observability.
Experience working in large-scale regulated environments.

Responsibilities

Design and govern the end-to-end telemetry ecosystem.
Establish how signals are generated, normalized, routed, and transformed into actionable intelligence.
Own the architecture and standards of the observability ecosystem.
Drive adoption of observability across platform, application, and security teams.
Define the target-state observability architecture, including standardized telemetry schemas, OpenTelemetry-based pipelines, and a unified signal model.
Architect end-to-end telemetry flows from instrumentation through collection, enrichment, routing, and persistence.
Ensure scalability, data integrity, and cost-efficient lifecycle management of telemetry.
Enable a centralized observability control plane for the enterprise.
Extend observability into the emerging AI domain, defining architectures that capture AI-specific signals.
Drive cross-layer architectural cohesion, aligning infrastructure, platform, application, and business observability.
Establish patterns for service-level indicators and objectives, distributed tracing, and intelligent telemetry pipelines.
Translate strategy into executable designs, defining standards, reference architectures, and implementation patterns.
Drive adoption across engineering teams to ensure consistency and scale.
Act as a technical authority, influencing platform direction and resolving complex design tradeoffs.
Ensure observability is embedded as a foundational capability for resilience, governance, and intelligent operations at scale.