AI Engineering Manager

Aspire Software company overview

Aspire Software operates and manages wholly owned software companies, providing mission-critical solutions across multiple verticals. By implementing industry best practices, Aspire delivers a time sensitive integration process, and the operation of a decentralized model has allowed it to become a hub for creating rapid growth by reinvesting in its portfolio.

About the job

The AI Engineering Manager leads a cross-functional team (Development & QA) and owns technical architecture, delivery outcomes, AI-enabled system design and driving an AI first culture among your team. This role is both strategic and hands-on. It requires strong expertise in modern AI frameworks, applied AI architectures, and scalable system design. The manager is accountable for delivering stable, secure, AI-powered capabilities — not just managing execution.

Core responsibilities

Technical leadership & architecture

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

AI framework & methodology expertise

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

Team leadership

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

Delivery & outcome ownership

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

AI-driven engineering excellence

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