AI Engineering Manager

🕒 March 20

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Aspire Software

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

☁️ SaaS

🏢 Enterprise

🤝 B2B

SaaS • Enterprise • B2B

Aspire Software is a company that focuses on acquiring and nurturing businesses with a strong foundation in outstanding products and passionate teams. As part of the Valsef Group, Aspire Software offers resources, knowledge, and a suite of best practices to enhance and expand operations for continuous improvement and sustainable growth. The company emphasizes decentralization to unlock innovation and adaptability within its acquired entities. Aspire Software is dedicated to serving its customers through long-term technology partnerships, leveraging capital and expertise in various verticals to grow both the businesses and individuals involved.

📋 Description

• Own product architecture, including AI/LLM-integrated components • Design scalable, secure, and maintainable systems • Lead decisions involving: • - LLM integration (OpenAI, Azure OpenAI, etc.) • - RAG architectures and vector databases • - AI orchestration frameworks (LangChain, Semantic Kernel, LlamaIndex) • Ensure system reliability, observability, and cost efficiency • Establish AI governance and safe usage practices • Apply modern AI methodologies, including: • - Retrieval-Augmented Generation (RAG) • - Prompt engineering and evaluation • - AI output validation and guardrails • - Human-in-the-loop workflows • - Model monitoring and performance evaluation • Drive experimentation, A/B testing, and telemetry-based decision making • Lead and mentor developers and QA engineers • Raise AI literacy across the team • Establish AI-native coding and review standards • Balance speed, quality, and architectural integrity • Own predictable, high-quality releases • Ensure AI features are measurable, validated, and production-ready • Act as technical escalation point • Drive cross-team alignment with Product, Data, and DevOps • Leverage AI-assisted development tools to improve velocity • Optimize AI cost-performance tradeoffs • Embed automation into testing and CI/CD pipelines

🎯 Requirements

• 7+ years software engineering experience, 2+ years in technical leadership • Hands-on experience building and deploying AI-enabled systems • Strong knowledge of: • - LLM integration and prompt design • - RAG architectures and vector search • - AI orchestration frameworks • - Cloud platforms (Azure, AWS, or GCP) • Experience designing scalable distributed systems • Preferred • - Experience in regulated industries • - AI governance and compliance knowledge • - Model lifecycle management and monitoring tools