Senior Principal Engineer, Agentic Systems

In this role you will own the technical architecture and engineering leadership for a product within an AI-native product line at Advisor360°, a leading enterprise wealthtech platform. You’ll lead the engineering side of a 5-person autonomous team, taking full ownership of architecture, quality, and technical decision-making. This is a true player-coach role where you not only design and build critical parts of the system, but more importantly elevate the effectiveness of both your team and AI agents through the systems and patterns you create. In doing so, you’ll help define what agentic software development looks like in practice and play a key role in shaping a new model for how modern B2B software gets built.

Here’s What You’ll Do:

Own the technical architecture for your team's product surface — service boundaries, data flow, API design, infrastructure decisions, and scaling strategy for large-scale SaaS
Review and approve product specifications before build begins — your job is to ensure specs give both humans and AI agents enough technical context to execute well
Author and maintain the team's agentic ecosystem — CLAUDE.md files, MCP server configurations, custom slash commands, agent hooks, and workflow templates. These artifacts teach AI agents how to work in your codebase and are the single most leveraged system you own
Build and own the AI-powered test automation pipeline — consume the Product Lead's user stories and acceptance criteria to drive automated e2e test generation, regression suites, and CI-integrated quality gates
Review agent-generated code for architecture alignment, security, performance, and correctness — agents produce volume, you provide judgment
Run the compound loop — after each feature ships, encode what worked and what didn't back into the system so agents and engineers get better with every cycle
Make architecture decisions that hold up at scale — real-time data processing, cloud-native infrastructure, API design for high-throughput environments
Write code selectively — architecturally novel problems, security-critical paths, and reference implementations that set the patterns agents follow
Direct AI agents on well-scoped implementation tasks while personally handling the work that requires deep system understanding
What You Bring to the Table:

8+ years as a software engineer, with at least 2 years in a tech lead, staff engineer, or architect role at a large-scale B2B SaaS company
Deep architecture experience — you've designed and shipped systems involving real-time data processing, cloud infrastructure, distributed services, and API-driven platforms
Strong cloud infrastructure depth — AWS (or equivalent), streaming architectures, large-scale data processing. You've built systems that handle significant throughput in production
Hands-on engineering ability — you can still build, not just draw diagrams. You write code when it matters
Experience with AI coding tools — you've used Claude Code, Cursor, or similar and have opinions on where agents help vs. where they fail
Strong system design instincts — can articulate *why* an architecture decision is right, not just *what* it is
Experience with AI technologies, LLMs, ASR, OCR, RAG
Experience designing automated pipelines that connect multiple systems (CI/CD, monitoring, alerting, data platforms) into cohesive engineering workflows
Comfort building with LLMs beyond code generation — agent orchestration, MCP integrations, tool-use patterns for engineering automation
Experience building test automation infrastructure — frameworks, e2e pipelines, CI-integrated quality gates
Preferred:
Hands-on experience with MCP (Model Context Protocol) or similar tool-integration patterns for LLMs
Experience with workflow orchestration platforms (Temporal, custom pipelines)
Background in financial services, wealth management, or regulated industries

The estimated base salary range for this position is $200,000 – $300,000 + bonus & equity.