Applied AI Engineering Lead

Backed by leading Silicon Valley investors, Peregrine helps public safety organizations, state and local and governments, federal agencies, and private-sector institutions address society’s challenges with unprecedented speed and accuracy. Our AI-enabled platform turns siloed and disconnected data into operational intelligence - instantly surfacing mission-critical information to empower better, faster decisions that improve outcomes at every touchpoint. Today Peregrine supports hundreds of customers across 30+ states and two countries, serving more than 125 million people - and we’re amplifying our impact as we expand into the enterprise and internationally.

The Role

Peregrine builds an end-to-end intelligence platform. As the Applied AI Engineering Lead, you will own how artificial intelligence is applied, evaluated, and operationalized across our product, turning complex data into trusted, explainable, and high-impact capabilities used in the field.

This role is about production AI in high-consequence environments. You’ll lead to develop AI-powered features that help customers detect risk, surface insights, and make faster, better decisions while maintaining high reliability, transparency, and performance.

What You’ll Do

Build AI-Powered Product Capabilities

• Lead the design and deployment of customer facing AI features across Peregrine’s platform
• Translate real operational problems into deployable AI-powered solutions
• Partner deeply with Product, Deployment Strategists, and other Engineering teams to integrate AI into core workflows

AI/ML Foundations

• Own and guide fine tuning strategies and reinforcement learning to improve decision quality
• Make principled tradeoffs between classical ML, deep learning, and LLM-based approaches based on accuracy, latency, and risk

AI Infrastructure

• Shape Peregrine’s AI infrastructure, including:
• Training and inference pipelines
• Model serving, versioning, and rollback
• Integration with real-time and batch data systems

Evaluation, Trust, and Quality

• Define and operate robust evaluation frameworks
• Establish quality standards that reflect real-world decision impact, not just model accuracy
• Own monitoring, drift detection, and failure analysis for deployed models

Leadership & AI Strategy

• Build and lead a high-performing Applied AI/ML team
• Set technical direction for applied AI across Peregrine
• Partner with executive leadership on AI strategy, roadmap, and responsible deployment

What We’re Looking For

Required

• Demonstrated experience shipping AI-powered features into production, ideally in enterprise or mission critical environments
• Hands-on experience with model fine tuning (LLMs or deep learning models)
• Practical exposure to reinforcement learning
• Experience in designing and operating AI/ML infrastructure
• Direct ownership of model evaluation, experimentation, and quality measurement
• Strong software engineering fundamentals as a lead

Strong Plus

• Experience working with large scale and/or real-time data platforms.
• Background in domains where trust, explainability, and reliability matter (e.g., public sector, security, healthcare, finance)
• Led software engineering teams before

What Success Looks Like

• AI features are deeply embedded in Peregrine’s core product and relied on by customers
• AI is applied to generate outcomes that are measurable, monitored, and improving over time
• Make AI a force multiplier both internally and externally

Salary Range: $225,000 - $320,000 Annually + Benefits + Equity (if applicable) + Bonus (if applicable)

Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, certifications or licenses, and specific work location. Information on the benefits offered is here.

Peregrine Technologies is committed to creating an inclusive environment for all employees. We celebrate diversity and are a proud equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.