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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Deployment Engineer - **Company:** The Stable - **Location:** New York, NY, United States - **Experience:** Experienced - **Salary:** $150,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Accounting Systems, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Audit Trail, Microsoft Azure, Business Systems, Databases, Relational Databases, Identity and Access Management, Python (Programming Language), Key Management, Regression Testing, Standard Sql, Software Deployment, Software Engineering, SQL Databases, Systems Integration, TypeScript, Google Cloud, Large Language Models, Prompt Engineering, Deployment Automation, Production Code, Operational Systems, Data Management - **Published:** May 16, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=4632ab6a32c1cdf5 ## About the Role Do you have experience in SQL?, * 4+ years of professional software engineering experience * Strong Python engineering experience * Strong SQL and relational database fundamentals * Hands-on experience building with modern LLM systems, including: + RAG + vector retrieval + agent workflows + tool/function calling + prompt engineering * Experience building and maintaining production systems * Experience integrating with third-party APIs and business systems * Strong communication skills with both technical and non-technical stakeholders * Security-minded engineering approach and strong ownership mentality Preferred Experience: * TypeScript * AWS, Azure, and/or GCP infrastructure * AI deployments in regulated or security-sensitive environments * Evaluation frameworks, regression testing, monitoring, and model performance tracking * Experience working with accounting, financial, or operational systems * Client-facing consulting or implementation experience ## Description This is not a role where you inherit a mature playbook and simply execute predefined processes. As an early member of the team, you will help shape how the practice operates - including how projects are scoped and delivered, how AI systems are deployed securely, how engineering reviews and documentation are handled, and how repeatable processes are built as the team grows. We are looking for someone who enjoys building both systems and structure: someone comfortable writing production code, deploying AI into complex client environments, and helping establish the engineering standards, deployment patterns, and operational discipline that future team members will follow. The systems we build support real operational workflows across finance, accounting, reporting, and back-office infrastructure. These are production environments where reliability, security, auditability, and thoughtful engineering matter. What You'll Do: * Design and deploy AI-powered applications, agents, RAG systems, workflow automations, and integrations. * Build production systems using Python, APIs, databases, and modern LLM tooling. * Integrate with CRMs, ERPs, accounting systems, internal APIs, and data platforms. * Deploy solutions into client cloud environments, private infrastructure, and secure production systems. * Build monitoring, testing, evaluation, and operational support processes for deployed AI systems. * Implement security-first engineering practices including IAM, secrets management, audit trails, and least-privilege access. * Participate in client discussions, technical reviews, implementation planning, and delivery. * Create technical documentation, deployment runbooks, and operational procedures. * Help establish the engineering and delivery standards for a growing AI practice. ## Related Videos - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Do TypeScript without TypeScript](https://www.wearedevelopers.com/videos/327-do-typescript-without-typescript) - [Resilient by Design: Building Robust Architectures in High-Stakes Financial Systems](https://www.wearedevelopers.com/videos/2106-resilient-by-design-building-robust-architectures-in-high-stakes-financial-systems) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Postgres in the Age of AI (and Devin)](https://www.wearedevelopers.com/videos/1042-postgres-in-the-age-of-ai-and-devin) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix)