Engineering Manager – Product Security
Rockwell Automation
CloudCyber Security
Senior Engineering Manager
Jump - Advisor AI
full-time
Posted on:
Location: Utah • 🇺🇸 United States
Visit company websiteSalary
💰 $180,000 - $270,000 per year
Job Level
Senior
Tech Stack
AWSAzureCloudElixirGoogle Cloud PlatformKubernetesTerraform
About the role
- Lead an engineering team building AI solutions for financial advisors
- Manage, mentor, and grow a team of 5-10 software engineers
- Conduct regular 1:1s, performance reviews, and career development discussions
- Foster a culture of technical excellence, kindness, and hard work
- Lead hiring efforts including sourcing, interviewing, and onboarding
- Define technical roadmaps and delivery timelines with product management
- Oversee system architecture decisions for scalability, reliability, and security
- Ensure engineering best practices: code reviews, testing, CI/CD, documentation
- Balance technical debt with feature velocity in a startup environment
- Drive AI/ML infrastructure and model deployment decisions
- Collaborate with compliance, security, and customer success teams
- Track and report engineering metrics and KPIs
- Identify and mitigate technical risks and bottlenecks
- Ensure on-time delivery of high-quality software releases
Requirements
- 7+ years of software engineering experience with at least 2 years in engineering management
- Strong technical background with hands-on experience in modern programming languages
- Experience building and scaling production systems, preferably in fintech, AI/ML, or B2B SaaS
- Proven track record of hiring, developing, and retaining engineering talent
- Experience with cloud platforms (AWS, GCP, or Azure)
- Excellent communication skills with ability to work effectively with both technical and business stakeholders
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
- Preferred: Experience in financial services or fintech, understanding of compliance requirements (SOC 2, GDPR, etc.)
- Preferred: Background in AI/ML engineering or working closely with data science teams
- Preferred: Experience with LLMs, RAG systems, or other modern AI architectures
- Preferred: Track record of building engineering teams from 5 to 20+ people
- Preferred: Experience in early-stage startups (Series A-C)
- Preferred: Knowledge of financial advisory workflows and tools
