Job Title: Integrations & Automations Developer (Python / AWS)

Location: Remote US (EST) (Inhouse Lakewood - Preferred)

Position Type: Full Time; 40 Hours

Company: 100 Boulevard Management

About the Role

We're seeking a results-driven AI Integrations & Automations Lead to guide a small, high-performance engineering team building intelligent automation systems for our eldercare and healthcare operations.

This role blends hands-on Python engineering, AI automation, and technical leadership. You'll oversee two AI Automation Developers—driving clarity, prioritization, and rapid delivery from concept to production. The ideal candidate thrives in fast execution cycles, makes smart tradeoffs, and knows when to iterate versus when to ship.

You'll work at the intersection of Python/AWS engineering, LLM-powered automation, and secure, scalable system design. Your responsibilities include building reusable SDKs, CI/CD pipelines, secure infrastructure, and self-improving AI workflows.

Day to day, you'll build microservices and backend scripts that automate business processes across our platforms—from scraping websites and integrating APIs (Twilio, DocuSign, etc.) to parsing documents and filling PDFs. You'll partner with internal teams to design and deploy automations that make a real-world impact.

Key Responsibilities

• Lead and mentor two AI Automation & Integration Specialists—driving focus, clarity, and fast execution.
• Design and oversee secure Python-based automations and integrations (Twilio, DocuSign, Gemini, OpenAI, etc.).
• Ensure security and compliance across all AI pipelines—encryption, credential management, and HIPAA/PHI standards.
• Build reusable SDKs and promote Infrastructure-as-Code (IaC) and CI/CD practices for scalable deployment.
• Own sprint planning and execution through clear prioritization, measurable outcomes, and rapid iteration cycles.
• Apply LLMs (OpenAI, Gemini, Google GenAI) and orchestration frameworks (LangChain) to automate workflows and decision support.
• Implement human-in-the-loop reviews and feedback loops that enable models to learn and improve over time.
• Partner with engineering, operations, and leadership to drive continuous automation improvements.