BravoTECH · 17 hours ago
Lead Software Engineer - AI/ML & Dynamic Pricing
Grapevine, TX
Full-time
Onsite
Lead/Staff
$160K/yr - $180K/yr
9+ years expBravoTECH is focused on intelligent commerce and revenue optimization, and they are seeking a Lead Software Engineer specializing in AI/ML and Dynamic Pricing. This role involves architecting and operationalizing machine learning-driven pricing systems to enhance revenue and competitive positioning, while ensuring real-time execution at scale.
Enterprise SoftwareHuman ResourcesInformation TechnologyProject ManagementStaffing Agency
Hiring Manager
Andrea Lee
Responsibilities
Architect and implement ML models for dynamic pricing, demand forecasting, elasticity modeling, and price optimization
Select and apply appropriate pricing algorithms (not generic ML approaches) based on business objectives and competitive landscape
Operationalize models into production systems with strict latency and availability constraints
Implement model explainability, monitoring, drift detection, and retraining workflows in live environments
Design feedback loops (including market and social data signals) to continuously improve pricing intelligence
Own and evolve a real-time pricing engine integrating multiple external and internal data streams:
Competitive data feeds
Web scraping pipelines
Transactional and behavioral data
Market and demand signals
Build safeguards and validation frameworks for revenue-critical price changes
Balance margin optimization, competitive response, and customer experience in algorithm design
Reduce decision latency from signal ingestion to pricing execution
Build high-throughput data pipelines for structured and unstructured pricing inputs
Design distributed systems to process real-time event streams and scraped market data
Integrate ML outputs into transactional eCommerce systems (checkout, rewards, promotions, payments)
Ensure SLA-driven availability, resilience, and observability across pricing infrastructure
Shape and modernize the AI-enabled backend stack (AWS, Kubernetes, microservices, CI/CD, observability)
Establish best practices for ML lifecycle management and production readiness
Mentor engineers on scalable backend architecture and ML integration
Act as technical owner for revenue-critical pricing systems
Qualification
Required
9+ years of backend or distributed systems engineering experience
Proven ownership of a dynamic pricing engine with multiple real-time pricing inputs
Experience deploying ML models into low-latency, production decisioning systems
Experience integrating ML outputs into revenue-impacting transactional workflows
Experience ingesting and processing real-time external market or scraped data
Hands-on experience with pricing optimization models
Hands-on experience with elasticity modeling
Hands-on experience with demand forecasting
Hands-on experience with revenue optimization algorithms
Ability to determine the appropriate modeling strategy for pricing scenarios (not applying generic ML patterns)
Experience operationalizing ML models (versioning, monitoring, drift detection, retraining)
Experience feeding structured and unstructured data—including social and external market signals—into ML and GenAI workflows
Strong backend development expertise in Java / Spring
Solid Python experience for ML model development and experimentation
Deep AWS experience (compute, storage, networking, managed services)
Kubernetes and containerized microservices architecture
CI/CD and DevOps practices for ML-enabled systems
Experience building highly available, high-throughput distributed systems
Strong eCommerce or retail technology experience
Experience building systems that directly influence revenue, pricing strategy, or margin optimization
Company
BravoTECH
BravoTech is a dynamic company that specializes in offering a complete range of IT staff augmentation and project management services.
201-500 employees
Funding
Current Stage
Growth StageLeadership Team
Kevin Beattie
Chief Financial Officer
Rob Duhon
Chief Operating Officer
Company data provided by crunchbase