Sr. Applications Engineer Full Time NEW

About Algebra  

Algebra builds and operates AI-powered workflows for mid-market companies as a managed service. We identify high-value operational processes, design AI systems to run them, and own the outcome end to end. We are not consultants. We do not sell software licenses. We are the accountable operator.

The Role  

This is a senior application engineering role for someone who can turn messy business workflows into working software systems.

You will build the internal and client-facing applications that sit around Algebra’s AI workflows: dashboards, workflow interfaces, approval screens, admin tools, integrations, and the application layer that makes our agents usable in the real world.

This is not a role where you will be handed perfect product specs. You will work from business problems, client workflows, rough product direction, and operational requirements. Your job is to translate that into reliable, usable, production-grade applications.

You need to be strong enough technically to own architecture, but practical enough to ship. You should be comfortable moving across frontend, backend, integrations, databases, APIs, authentication, permissions, and production debugging.

This is a builder role. There is no large product engineering org around you. You will help define the patterns, standards, and application architecture Algebra uses as it scales from custom client deployments into repeatable systems.

If your instinct is to understand the workflow first, then build the simplest system that makes it run better – this is the role.

What You’ll Do  

Application Development  

• Build production-grade applications that support Algebra’s AI-powered workflows  
• Create dashboards, workflow interfaces, approval tools, admin panels, and operational systems  
• Design application flows that make AI outputs reviewable, editable, auditable, and usable by humans  
• Build internal tools that help Algebra deploy, monitor, and manage client workflows  
• Work across frontend, backend, databases, APIs, authentication, permissions, and integrations  
• Turn ambiguous business requirements into working software without needing every detail pre-defined  

Workflow and Product Engineering  

• Translate real client processes into clear application logic and user flows  
• Build interfaces for document intake, workflow routing, approvals, exceptions, reporting, and human-in-the-loop review  
• Work closely with AI engineers to connect model outputs into usable product experiences  
• Design systems that support both automation and human control  
• Create reusable application patterns for repeatable client use cases  
• Improve the product layer so Algebra does not rebuild everything from scratch for every client  

Integrations and Systems  

• Build and maintain integrations with client systems, tools, databases, CRMs, ERPs, communication platforms, and document repositories  
• Design reliable API flows between Algebra, client systems, and third-party services  
• Handle authentication, permissions, webhooks, data syncing, and integration failure states  
• Debug production issues across application code, data flows, integrations, and infrastructure  
• Work with cloud and DevOps engineering to make sure applications deploy cleanly and run reliably  

Engineering Quality  

• Own technical decisions across application architecture, code quality, testing, and maintainability  
• Set standards for how Algebra builds applications across client deployments  
• Improve developer workflows, reusable components, and shared engineering patterns  
• Write clean, practical code that another strong engineer can understand and extend  
• Identify technical debt early and fix it before it slows delivery  
• Balance speed with reliability, especially when client workflows depend on what we build  

What We’re Looking For  

• 10+ years of experience in application engineering, full-stack engineering, backend engineering, or product engineering  
• You have built and shipped production applications used by real customers or internal operators  
• Strong experience across modern web application development, including frontend, backend, APIs, databases, and authentication  
• You are comfortable working across the stack and do not need to be protected inside a narrow specialty  
• You can turn unclear requirements into a working product without waiting for perfect specs  
• You understand application architecture, data models, permissions, workflow logic, and integration patterns  
• You can debug complex issues across product, backend, API, database, and third-party systems  
• You write clear, maintainable code and know when to refactor versus when to ship  
• You can communicate clearly with founders, engineers, product leads, and client-facing teams  

Bonus Points  

• You have built workflow software, internal tools, approval systems, admin platforms, or operational dashboards  
• You have experience building applications around AI, automation, LLMs, or agent-based systems  
• You have worked with document processing, data extraction, human-in-the-loop review, or exception handling workflows  
• You have built integrations with systems like Salesforce, HubSpot, Zoho, Microsoft 365, Google Workspace, Slack, Teams, SharePoint, or ERP tools  
• You understand multi-tenant architecture, role-based access control, audit logs, and enterprise permissions  
• You have worked in a startup, services-led technology company, or client-facing product environment  

What This Role Is Not  

This is not a narrow frontend or backend role. You need to understand the full application layer and how the pieces connect.

This is not a role where product hands you polished tickets and you quietly execute. You will be expected to understand the workflow, form a view, and build what actually works.

This is not a pure AI engineering role. The value is in making AI outputs usable, reliable, and actionable inside business processes.

This is not a maintenance role inside a mature platform. You will help create the application architecture, reusable patterns, and product foundation the company scales on.

If your best work requires a large product team, detailed specs, and stable requirements, this is probably not the right fit. If you want to build the application layer of an AI operations company from the ground up – we want to talk.