Senior Application Engineer

About Algebra

Algebra operates AI-driven workflows for mid-market businesses as a managed service provider. Instead of offering consultancy or software licenses, Algebra takes full accountability by identifying key operational processes, creating AI systems to manage them, and overseeing the entire outcome.

Role Overview

This senior application engineering position focuses on transforming complex, disorganized business workflows into functional software applications. You will be responsible for developing both internal and client-facing software components that support Algebra's AI workflows, including dashboards, workflow interfaces, approval systems, admin tools, and integrations. The role entails crafting the application layer that makes AI agents practical and usable in real-world scenarios.

This position requires working with business challenges, client workflows, and provisional product directions rather than precise specifications. You will translate these into robust, user-friendly, production-grade applications. The ideal candidate is technically proficient enough to lead architecture design, yet pragmatic enough to deliver working software promptly. Proficiency across frontend, backend, integrations, databases, APIs, authentication, permissions, and production troubleshooting is essential.

This is a creator’s role, with limited existing product engineering framework. You'll have the opportunity to establish standards, patterns, and application architecture as Algebra evolves from custom client solutions to standardized, scalable systems. The core approach is to thoroughly understand workflows first, then engineer the simplest system that improves operational efficiency.

Key Responsibilities

• Develop production-ready applications supporting Algebra’s AI-powered workflows including dashboards, workflow and approval interfaces, admin panels, and operational systems.
• Design application flows enabling human interaction—allowing AI outputs to be reviewed, edited, audited, and effectively utilized.
• Create internal tools facilitating deployment, monitoring, and management of client workflows.
• Work across technology stacks including frontend, backend, database management, API development, authentication systems, permissions, and integration mechanisms.
• Convert ambiguous business requirements into functional software without detailed upfront specifications.
• Map actual client processes into clear application logic and user workflows.
• Develop interfaces handling document intake, workflow routing, approvals, exceptions, reporting, and human-in-the-loop reviews.
• Collaborate with AI engineers to integrate model outputs into user-friendly product experiences highlighting both automation and manual oversight.
• Design reusable application patterns for replicable client scenarios to avoid rebuilding solutions from the ground up for each deployment.
• Build and sustain integrations with client software systems like CRMs, ERPs, communication tools, and document repositories.
• Establish robust API communication flows between Algebra, client platforms, and third-party services, managing authentication, webhooks, data synchronization, and failure recovery.
• Investigate and resolve production issues spanning applications, data pipelines, integrations, and infrastructure.
• Coordinate with cloud and DevOps teams to ensure smooth deployment and reliable operation of applications.
• Lead technical decisions on application architecture, implementing coding standards, testing procedures, and maintainability protocols.
• Define development standards across all client deployments to foster consistency and quality.
• Enhance developer productivity by improving workflows, reusable components, and engineering patterns.
• Produce clean, practical, and maintainable code comprehensible to other skilled engineers.
• Identify and remediate technical debt early to avoid delivery delays.
• Balance delivery speed with system reliability, especially given client dependency on these workflows.

Candidate Profile

• Possess over 10 years of experience in application, full-stack, backend, or product engineering roles.
• Proven track record of building and deploying production-grade software for real users or internal operators.
• Expertise in modern web development encompassing frontend, backend, APIs, database design, and authentication mechanisms.
• Comfortable as a versatile engineer who can operate across various technology layers rather than focusing on a single specialty.
• Adept at transforming vague requirements into functional products without waiting for ideal specs.
• Deep understanding of application architecture, data structures, permission models, workflow logic, and integration strategies.
• Skilled in diagnosing complex problems across product, backend services, APIs, databases, and third-party integrations.
• Capable of writing straightforward, maintainable code with sound judgement on refactoring versus shipping.
• Effective communicator able to collaborate with founders, engineers, product managers, and customer-facing teams.

Additional Preferred Qualifications

• Experience creating workflow management tools, internal platforms, approval systems, admin dashboards, or operational interfaces.
• Familiarity working with AI technologies, automation, large language models, or agent-based systems.
• Background in document processing, data extraction techniques, human-in-the-loop workflows, and exception management.
• Knowledge of integrating with widely-used systems such as Salesforce, HubSpot, Zoho, Microsoft 365, Google Workspace, Slack, Teams, SharePoint, or ERPs.
• Understanding of enterprise-grade features including multi-tenant architectures, role-based access control, audit trails, and complex permissions.
• Prior experience in startup environments, service-driven technology firms, or client-centric product companies.

Role Clarifications

This role goes beyond narrow frontend or backend responsibilities, requiring comprehension of the entire application stack and the connections between components. It involves proactive engagement to grasp workflows, form judgements, and build solutions that truly work rather than passively executing finished product specifications. This is not focused on AI engineering alone but on making AI-generated outputs practical and actionable within business contexts. It is not a maintenance role for mature platforms; rather, it demands developing foundational application architectures and reusable components for scaling. Candidates seeking large teams, detailed specs, or stable requirements may find this opportunity unsuitable. However, if you are motivated to design and build the application layer for an AI operations company from inception, this position aligns well with your aspirations.