About the Team 

The Tax Artificial Intelligence Manager leads the engineering team responsible for building and evolving an AI-enabled application platform that supports document processing, workflow automation, AI-assisted analysis, and internal and external user-facing applications for tax. This role sits at the intersection of software architecture and AI/technology execution, partnering with product owners, business subject matter experts (SMEs), security, and infrastructure teams to translate real “jobs to be done” into secure, scalable, enterprise-grade software. 

Tax domain knowledge is not required. The successful candidate should be comfortable learning business workflows from subject matter experts and translating those workflows into reliable software systems. You will own technical direction across backend services, asynchronous processing, AI integrations, cloud infrastructure, data persistence, security, and observability, balancing speed, quality, risk, and maintainability. 

What You’ll Do 

Architecture & Technical Leadership 

• Lead the architecture, design, and delivery of AI-enabled software products and internal platforms, owning decisions across backend services, async processing, AI integrations, cloud, data, and security. 

Team Leadership & Mentorship 

• Manage and mentor software engineers, quality assurance professionals, and business analyst, providing technical guidance, code review, delivery planning, and career development. 

Cloud & Platform Engineering 

• Own cloud architecture on Microsoft Azure, including async and event-driven workloads, background jobs, and reliable, cost-effective operations. 

Security & Data Protection

• Ensure secure handling of data, secrets, authentication, authorization, tenant isolation, encrypted storage, and auditability.

Delivery & Engineering Excellence

• Improve engineering practices around testing, CI/CD, monitoring, deployment, documentation, and operational support.

Architecture & Delivery

• Establish development standards for clean architecture, dependency injection, async design, and API consistency.

• Maintain and evolve a Python/FastAPImonorepo with multiple application services and shared packages.

• Make pragmatic architecture decisions that balance speed, quality, risk, and long-term maintainability.

Team Leadership

• Coach and develop engineers, quality assurance professionals, and businessanalyst, supporting career growth and strong delivery habits.

• Run code reviews, delivery planning, and technical guidance that raise the quality bar across the team.

• Partner with product owners and business SMEs to translate ambiguous needs into clear, deliverable technical work.

AI Integration & Document Processing

• Guideintegrations with Azure Foundry, Azure AI Document Intelligence, and other Azure resourcesacross document-processing and AI-assisted analysis pipelines.

• Establish responsible, repeatable patterns for prompting,embeddings, semantic search, and AI evaluation within controlled enterprise tools.

Cloud, Async & Operations

• Oversee asynchronous job processing using Azure Service Bus and Azure Functions.

• Support production troubleshooting, performance tuning, cost management, and reliability improvements.

• Strengthen observability through structured logging, tracing, and Azure Monitor / Application Insights.

Security & Compliance

• Ensure secure handling of data, secrets, identity, authorization, tenant isolation, encrypted storage, and audit logging.

• Partner with security and compliance stakeholders on identity, access, and responsible-use standards.

Stakeholders & Collaboration Model 

This role partners across: 

• Development team (direct reports, delivery owners) 

• Product owners and business/tax SMEs (requirements, prioritization, workflows) 

• Security, compliance, and infrastructure teams (identity, governance, approved tooling) 

• Client-facing and leadership stakeholders (roadmap, delivery commitments, business outcomes) 

Technology Environment 

Our platform is built on the following stack. Depth across every item is not expected; familiarity with the core backend and Azure ecosystem matters most. 

Core Backend & Data 

• Python 3.12+, FastAPI, and async-first service design (AsyncIO) 

• Pydantic / Pydantic Settings; Uvicorn / Gunicorn 

• SQLAlchemy (async ORM) with Alembic migrations 

• Azure PostgreSQL 

Cloud & Platform (Microsoft Azure) 

• Azure App Service and Azure Functions 

• Azure Service Bus for async, queue-based processing 

• Azure Blob Storage and Azure Key Vault

• Azure API Management and Managed Identity

• Azure Monitor / Application Insights

AI & Document Processing

• AzureFoundryand the OpenAI Python SDK (chat and embeddings)

• Microsoft Agentic Framework; Azure AI Document Intelligence

• FAISS, scikit-learn, andRapidFuzzfor semantic search and matching

• PyMuPDF/ pypdf, pandas, andnumpyfor document and data processing

Security & Identity

• Microsoft Entra ID / Azure AD and Okta

• OAuth2 / OIDC, JWT, and machine-to-machine API authentication

• Key Vault-backed secrets, encrypted storage, tenant isolation, and audit logging

DevOps, Testing & Observability

• Azure DevOps Pipelines and Octopus Deploy; Veracode scanning