Cloud DB Architect / ML & Agentic AI Engineer

KNUFF & KUNDE PLLC
Eagle, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Part-time / full-time
Working hours
Shift work
Languages
English

Job location

Eagle, United States of America

Tech stack

API
Artificial Intelligence
Software as a Service
Cloud Computing
Cloud Engineering
Data Infrastructure
Data Integrity
DevOps
Design of User Interfaces
Python
PostgreSQL
Linux System Administration
Query Optimization
Role-Based Access Control
Large Language Models
Backend
FastAPI
Data Layers
Virtual Agents
Docker

Job description

We're building proprietary AI software for our accounting firm, transitioning our internal tools into a multi-tenant SaaS platform. Independently funded with no outside investors - you'll have the runway to build this the right way, not the fastest way. You'll join our developer and UI/UX designer to own the cloud architecture, data infrastructure, and agentic AI systems end-to-end.

What You'll Own

Agentic AI Workflows Design and harden autonomous AI agents (Vertex AI, Claude) that reliably execute multi-step financial workflows - with validation layers, fallback logic, and guardrails against hallucination and context drift.

Cloud Infrastructure Architect the migration from a local environment to a secure, scalable, multi-tenant cloud deployment ready for external firms to onboard.

Data Layer Design and optimize PostgreSQL schemas handling complex financial data alongside vector-based AI memory (pgvector) - with zero tolerance for data integrity issues., * How do you engineer agentic workflows against external APIs (Vertex/Claude) so they reliably execute multi-step tasks without hallucinating or losing context?

  • How do you balance rapid MVP deployment against the strict data privacy requirements of sending financial PII to an external AI provider?

Requirements

AI Systems

  • Production experience building agentic workflows against Vertex AI and/or Claude APIs
  • Strong grasp of RAG architecture and retrieval strategies
  • Practical techniques for constraining LLM outputs - structured outputs, tool-use validation, state tracking across multi-turn tasks, and recovery/fallback logic when a step fails or hallucinates

Backend & Data

  • Python 3.10+, FastAPI, AsyncIO at a production level
  • PostgreSQL schema design for relational + JSONB data, query optimization, pgvector implementation and tuning

Cloud & DevOps

  • GCP experience strongly preferred
  • Docker, Linux administration, CI/CD pipeline design
  • Comfortable owning infrastructure decisions with minimal oversight

Security

  • "Secure by design" development practices
  • Encryption at rest/in transit, RBAC implementation
  • Experience architecting data-loss prevention boundaries - specifically around what does and doesn't leave your infrastructure when calling external AI APIs
  • Familiarity with compliance considerations for sensitive PII (financial data experience a plus)

Benefits & conditions

Pulled from the full job description

  • 401(k)
  • Health insurance
  • Health savings account
  • Flexible schedule, * 401(k)
  • Flexible schedule
  • Health insurance
  • Health savings account

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