Lead Software Engineer

Vertex Inc. is seeking a Lead Software Engineer to drive performance engineering, AI-driven automation, and technical leadership across their cloud-native SaaS platform. This role is highly hands-on and influential, focusing on designing scalable performance solutions and intelligent automation to improve engineering outcomes.

Responsibilities:

• Lead performance‑by‑design architecture and engineering decisions
• Design, build, and own AI‑powered performance engineering and automation solutions
• Architect and deploy LLM‑based agents and distributed workflows
• Develop and maintain scalable performance test frameworks integrated into CI/CD
• Embed with product teams to translate business goals into actionable performance outcomes
• Diagnose and resolve complex performance issues across the SDLC
• Mentor engineers and elevate performance and automation maturity across teams

Requirements:

• Bachelor's degree in Computer Science, Engineering, or equivalent experience
• 8–10 years experience in software and performance engineering
• 3+ years building cloud‑native SaaS systems
• Demonstrated success leading technical initiatives and mentoring engineers
• Proven ability to lead architecture and engineering decisions
• Experience mentoring engineers and setting technical standards at scale
• Hands‑on development of production‑grade systems and automation
• Strong foundation in modern, object‑oriented languages (C#, Java, Go, or similar)
• Expert use of GitHub for collaboration, branching strategies, reviews, and automation
• Version‑controlled test and automation infrastructure
• Designing and maintaining reusable, scalable performance test frameworks
• CI‑integrated performance validation and regression detection
• Instrumentation of systems and tests using metrics, logs, and traces
• Data‑driven diagnosis of latency, throughput, and bottlenecks
• Practical understanding of prompt design and structured prompting
• Ability to work effectively with LLM APIs and AI tooling
• Designing and operating distributed workflows (AI agents + tool calling)
• Experience orchestrating complex automation pipelines
• Using AI to generate test scenarios, code artifacts, and manifests
• Focus on accelerating delivery while maintaining quality and governance
• Designing and operating cloud‑native SaaS systems
• Familiarity with Infrastructure as Code (Terraform, CloudFormation, Helm)
• Deep experience integrating automation into CI/CD pipelines
• GitHub Actions, Azure DevOps, Jenkins, or equivalent
• Applying guardrails, evaluation metrics, and quality controls to AI systems
• Ensuring reliability, safety, and repeatability of AI outputs
• Practical application of Little's Law, USL, Amdahl's Law
• Master's degree in Computer Science, Engineering, or equivalent experience
• Experience delivering AI/ML or Generative AI solutions in production strongly preferred
• Queueing theory experience strongly preferred