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 RolePeregrine 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 DoBuild AI-Powered Product CapabilitiesLead the design and deployment of customer facing AI features across Peregrine’s platformTranslate real operational problems into deployable AI-powered solutionsPartner deeply with Product, Deployment Strategists, and other Engineering teams to integrate AI into core workflowsAI/ML FoundationsOwn and guide fine tuning strategies and reinforcement learning to improve decision qualityMake principled tradeoffs between classical ML, deep learning, and LLM-based approaches based on accuracy, latency, and riskAI InfrastructureShape Peregrine’s AI infrastructure, including: Training and inference pipelinesModel serving, versioning, and rollbackIntegration with real-time and batch data systemsEnsure models are observable, scalable, secure, and cost-effective in productionMeet enterprise and government requirementsEvaluation, Trust, and QualityDefine and operate robust evaluation frameworksEstablish quality standards that reflect real-world decision impact, not just model accuracyOwn monitoring, drift detection, and failure analysis for deployed modelsLeadership & AI StrategyBuild and lead a high-performing Applied AI/ML teamSet technical direction for applied AI across PeregrinePartner with executive leadership on AI strategy, roadmap, and responsible deploymentWhat We’re Looking ForRequiredDemonstrated experience shipping AI-powered features into production, ideally in enterprise or mission critical environmentsHands-on experience with model fine tuning (LLMs or deep learning models)Practical exposure to reinforcement learningExperience in designing and operating AI/ML infrastructureDirect ownership of model evaluation, experimentation, and quality measurementStrong software engineering fundamentals as a leadStrong PlusExperience 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 beforeWhat Success Looks LikeAI features are deeply embedded in Peregrine’s core product and relied on by customersAI is applied to generate outcomes that are measurable, monitored, and improving over timeMake AI a force multiplier both internally and externallySalary 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.