Lead Applied AI Engineer - Real-Time Coaching & Insights

Orum ?; Austin (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

Orum is seeking an experienced senior AI/ML engineer to lead the design and delivery of AI-powered product features. You will build LLM-based coaching insights and real-time recommendations, architect low-latency systems, and define best practices across the engineering org.

You will partner with Product and Engineering to identify high-impact AI opportunities and build robust data pipelines to support use cases, while mentoring engineers to lift applied AI practices across teams.

Qualifications

• 7+ years of software engineering experience with strong hands-on AI and ML experience.
• Proven track record of shipping AI and ML systems into production.
• Experience building and deploying ML pipelines for training, inference, monitoring, and continuous improvement.
• Deep experience with LLMs and modern AI tooling, including prompting, RAG, embeddings, and agents.
• Experience training and fine-tuning models for domain-specific use cases.

Responsibilities

• Lead the design and delivery of AI-powered product features from idea to production.
• Build LLM-based systems for coaching insights and real-time recommendations during calls.
• Architect systems that support low latency and large-scale AI use cases.
• Define and implement AI and ML best practices across the engineering org.
• Partner with Product and Engineering to identify high-impact AI opportunities.
• Build scalable data and feature pipelines to support AI use cases.
• Establish evaluation, monitoring, and feedback loops to improve model performance.
• Mentor engineers and raise the bar on applied AI engineering practices.

Skills

AI/ML engineering

LLMs & AI tooling

System design

Data pipelines

Real-time intelligence

Experimentation

Tools

BigQuery

ClickHouse

Job description

Orum is seeking an experienced senior AI/ML engineer to lead the design and delivery of AI-powered product features. You will build LLM-based coaching insights and real-time recommendations, architect low-latency systems, and define best practices across the engineering org.

You will partner with Product and Engineering to identify high-impact AI opportunities and build robust data pipelines to support use cases, while mentoring engineers to lift applied AI practices across teams.