Enterprise Architect -- Product Engineering

About Asymbl

Asymbl is the workforce orchestration company bringing together recruiting technology to hire people, digital labor strategy to onboard digital workers, and platform expertise to bring it all together. We help businesses attract, design, manage, and scale a hybrid workforce that drives more meaningful business impact, faster.

We are building a company where human and digital workers operate as one coordinated system of work, and where go-to-market execution is as intentional as the products and services we deliver.

Position Overview

We are hiring an Enterprise Architect to set the architecture, data, and security direction for the Asymbl Intelligence platform. This isn't a whiteboard-only role. You will make the foundational decisions across our three current priorities: Talent Intelligence, Slack integration, and Rosa, our Agentforce-based digital worker. A Senior Developer will execute within the architecture you design, so your decisions need to be clear, documented, and built to hold up under real-world scale.

You design the system. You own the "why" behind every major technical choice, and you write it down.

Why Join Us?

At Asymbl, every architecture decision you make will shape how our platform scales, how safely our digital workers operate, and how fast our engineering teams can move. You’ll work at the intersection of enterprise systems and AI-native architecture, solving complex, high-impact problems that directly influence product and technology direction.

This is a role with real ownership—where you have a direct line to leadership and a team that executes on what you design, so your best thinking doesn’t stay on paper; it ships to production.

Responsibilities:

You will be responsible for defining and driving the end-to-end enterprise architecture across product engineering, ensuring scalable, secure, and future-ready systems aligned with business goals. This includes leading AI/GenAI strategy, platform architecture, and data design across complex, distributed environments.

You will own-

Talent Intelligence (TI)

Our data-heavy platform combines relational, graph, and AI-driven matching.

• Polyglot data architecture decisions: when to use relational, graph, or vector storage, and why
• Schema versioning and migration governance
• Scalability planning for large candidate and resume datasets
• Data security review across the platformSlack Integration

Connecting our digital workers to the platforms where people already work.

• Integration architecture patterns: authentication model and event flow design
• Build-vs-platform-native decisionsRosa (Asymbl Intelligence / Agentforce)

Our digital worker is built on both platform-native and custom foundations.

• Agent architecture strategy: Agentforce versus custom agent frameworks, and when each fits
• Multi-agent orchestration design
• Evaluation and observability strategy for AI systemsModel Context Protocol (MCP)

The connective tissue across all three priorities. We need real depth here, not passing familiarity.

• MCP server architecture decisions: which tools get exposed, with what scoping and permission boundaries per tool
• Security review of MCP integrations. A misconfigured MCP tool can leak context outside its intended scope. This is a known risk class, not a hypothetical, and we treat it that way.
• Build-vs-use decisions on MCP serversLLM Provider Strategy

Model-agnostic fluency, not brand loyalty.

• Vendor selection strategy per use case, weighing cost, latency, context window, output limits, and reasoning quality
• Abstraction layers that avoid vendor lock-in
• Fallback and redundancy strategy for provider outages and rate limits

Educational Qualification

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field
• Master's degree in a related field is a plus, not a requirement
• Equivalent hands-on experience matters as much to us as the degree. If you have architected real systems at scale, we want to hear about them.
• Relevant certifications are welcome but optional: Google Cloud Professional Cloud Architect, AWS Certified Solutions Architect, Salesforce Application/System Architect, TOGAF

Required Experience

• 10+ years of overall software engineering experience
• 4+ years in an architecture-level role (Enterprise Architect, Platform Architect, Principal Engineer, or equivalent) setting technical direction that other engineers execute against
• 3+ years designing and scaling data-intensive platforms across relational, graph, or vector data stores
• 2+ years of hands-on work with LLM-based systems in production: agent architectures, orchestration, evaluation, or provider integration
• Demonstrated experience owning security and data governance decisions, not just implementing them
• A track record of documented architecture decisions (ADRs or equivalent) that teams actually followed

What We Are Looking For

• Proven experience setting enterprise or platform architecture direction for data-intensive, AI-driven products
• Deep data architecture expertise across relational database management systems (RDBMS), graph databases, and vector/embedding stores, plus schema migration governance and data sync architecture
• Hands-on understanding of multi-agent systems, agent orchestration, and large language model (LLM) evaluation frameworks, including retrieval-augmented generation (RAG)
• Real depth in Model Context Protocol (MCP): server architecture, tool scoping, agent-tool permission boundaries, and context isolation
• Experience architecting for a multi-provider LLM world. The signal we are looking for: you have built something where swapping the underlying model (Claude, GPT, Gemini) doesn't mean rewriting the integration layer. Name-dropping providers isn't the bar. Multi-model architecture, model routing, cost-per-token optimization, and provider fallback design are.
• Integration architecture fluency: webhook and event-driven design, OAuth and token-based authentication, API design
• Cloud infrastructure depth on Google Cloud Platform (Cloud SQL, AlloyDB, Vertex AI, Pub/Sub, Cloud Functions, budget and cost governance) and Amazon Web Services (Lambda, DynamoDB, IAM-based authentication)
• A security-by-default mindset: authentication and authorization review, least-privilege design as a habit, not an afterthought
• Architecture documentation discipline. You write Architecture Decision Records (ADRs) because future engineers deserve to know why, not just what.

Nice to Have

• Salesforce platform experience, especially Agentforce (Apex, Lightning Web Components, Topics, Actions)
• Experience with agent development kits (ADK or equivalent)
• Prior work on talent, recruiting, or workforce technology platformsAsymbl is an equal opportunity employer. We welcome candidates from all backgrounds.