Senior Applied AI Engineer

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🕒 May 29

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Givzey

WebsiteLinkedInAll Job Openings

1 - 10 employees

💸 Finance

🤝 Non-profit

☁️ SaaS

Finance • Non-profit • SaaS

Givzey is a platform that offers intelligent solutions for the fundraising process, including smart gift agreements, dynamic workflows, automated pledge reminders, and intelligent invoicing. The company aims to streamline and scale multi-year giving and one-time gifts, enhancing the donor experience while providing tools for fundraising teams to improve efficiency. Givzey is utilized by educational institutions and other organizations to secure and manage donations effectively.

📋 Description

• Design, build, and maintain production-grade AI systems and customer-facing AI features • Develop agentic workflows using LLMs, retrieval systems, tools, APIs, and backend services • Build backend services, orchestration systems, automation, and infrastructure supporting AI-powered workflows • Design and implement retrieval-augmented generation (RAG) systems, including ingestion pipelines, embeddings, semantic retrieval, and context assembly • Integrate foundation models through platforms such as Amazon Bedrock or Agent Core • Develop robust prompting strategies, structured outputs, guardrails, and workflow logic for production use cases • Implement evaluation systems for prompts, agents, and workflows, including regression testing, trace review, golden datasets, and human QA processes • Monitor and improve production AI systems for quality, reliability, latency, observability, and cost efficiency • Debug AI behavior through logs, traces, evaluations, user feedback, and production telemetry • Collaborate closely with engineering, product, operations, and customer-facing teams to turn ambiguous requirements into reliable systems • Help establish strong engineering standards around testing, deployment, CI/CD, version control workflows, code review, and operational reliability • Mentor and collaborate with engineers across both software and AI disciplines • Evaluate emerging AI technologies pragmatically based on business impact, maintainability, and operational reliability

🎯 Requirements

• US Citizen or authorized to work in US • 5+ years of professional software engineering experience building production systems • Strong proficiency in Python • Strong backend engineering fundamentals and experience building scalable APIs, services, distributed systems, or workflow orchestration platforms • Proven hands-on experience building and shipping AI-powered applications using LLMs, generative AI APIs, agents, retrieval systems, or related technologies in production environments • Experience designing and implementing agentic workflows, tool-calling systems, structured outputs, prompt pipelines, or retrieval-augmented generation architectures • Strong understanding of the practical challenges involved in production AI systems, including hallucination mitigation, evaluation, reliability, observability, latency, and cost management • Experience building production software systems with strong engineering standards around testing, QA, deployment, monitoring, and maintainability • Strong understanding of modern software engineering practices, including Git workflows, code review, CI/CD, automated testing, operational debugging, and release management • Experience working with cloud infrastructure, preferably AWS • Experience working with SQL and/or NoSQL databases • Strong debugging, systems-thinking, and problem-solving skills • Ability to operate effectively in fast-moving environments with evolving requirements and imperfect information • Strong communication skills and ability to collaborate across technical and non-technical teams

🏖️ Benefits

• Health insurance • Retirement plans • Paid time off • Flexible work arrangements • Professional development