AI Engineer

HubSync • , (Multiple States)

4d

About The Position

HubSync is an end-to-end platform for tax and audit firms, handling document management, workflow automation, and AI-powered document processing. We are transforming HubSync into an AI-native platform with agentic AI capabilities across all our key modules. We are looking for an experienced backend engineer who has built and shipped production systems that real users depend on. Active areas of work where you will have direct ownership include agentic workflow orchestration, document intelligence at scale, workflow state management, evaluation and observability, cost-accuracy optimization, and trust and reliability.

Requirements

• 4+ years building and shipping backend systems in production environments where uptime and correctness matter
• A track record of delivering enterprise-grade features and products, from design through deployment and ongoing operations
• Deep experience with relational databases: PostgreSQL or equivalent, schema design, query optimization, data modeling, migrations
• Hands-on work with event-driven architectures: message queues, async processing, distributed job execution
• Production experience with AWS (Lambda, SQS, S3, ECS) or equivalent cloud platforms
• Comfort reading and writing both TypeScript and Python (or the ability and willingness to pick up a second language quickly)
• Experience with the full software delivery lifecycle: design, implementation, testing, deployment, monitoring, and incident response
• You work across the stack when the problem requires it. The boundaries between backend, data, infrastructure, and product work are not rigid here. The best work happens when engineers move between them based on what the problem demands.

Nice To Haves

• Exposure to agentic systems, agent orchestration frameworks, or multi-agent workflow design
• Familiarity with RAG architectures, vector databases, or document processing pipelines
• Experience with multi-tenant SaaS architecture (schema isolation, tenant-scoped data, access control)
• Background in document intelligence: OCR, structured extraction from PDFs, form understanding
• Open-source contributions, technical writing, or other public evidence of engineering depth

Responsibilities

• Agentic workflow orchestration: Multi-agent coordination across tax document workflows with human-in-the-loop oversight. Agent state machines, tool routing, context windowing, and retry semantics for processes that run for minutes or hours.
• Document intelligence at scale: Production-grade pipelines that extract, classify, and validate tax forms and financial documents across dozens of formats and quality levels.
• Workflow state management: State hydration for long-running agentic workflows, failure handling, checkpoint/resume, and recovery across distributed services.
• Evaluation and observability: Task completion rates, accuracy attribution, cost tracking per action, regression detection. Attributing outcomes to specific agent reasoning steps when something goes wrong.
• Cost-accuracy optimization: Optimizing cost, accuracy, and latency trade-offs across different document types, complexity levels, and client tiers during peak tax season volume.
• Trust and reliability: Making non-deterministic agent output trustworthy for professionals who cannot accept errors. Supervision layers, validation rules, human review gates.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed