Vertex Inc.

Vertex is a global biotechnology company that invests in scientific innovation.

Lead Software Engineer

Software EngineerSoftware EngineerFull TimeRemoteTeam 1,001-5,000

Location

United States

Posted

6 days ago

Salary

$138K - $180K / year

C#JavaGoGit HubGit Hub ActionsTerraformCloud FormationHelmAWSAzureGCPCi/cdDev OpsJenkinsPerformance TestingObservabilityLLMDistributed SystemsDockerKubernetes

Job Description

Job Description:

Lead Software Engineer (Performance Engineering + AI Automation)

Summary

Vertex is seeking a Lead Software Engineer to drive performance engineering, AI‑driven automation, and technical leadership across our cloud‑native SaaS platform. This role is highly hands‑on and highly influential—owning the design and delivery of scalable performance solutions, intelligent automation, and AI‑powered workflows that materially improve engineering outcomes.

You will serve as a technical authority and force multiplier, embedding with engineering teams to ensure performance, reliability, and scalability are built in from day one.

Must‑Haves / Non‑Negotiables

Candidates must demonstrate strong, real‑world experience in the areas below. These are critical to success in this role.

Leadership & Technical Influence Across the Organization

  • Proven ability to lead architecture and engineering decisions
  • Experience mentoring engineers and setting technical standards at scale

Advanced Software Engineering & Automation

  • Hands‑on development of production‑grade systems and automation
  • Strong foundation in modern, object‑oriented languages (C#, Java, Go, or similar)

GitHub & Repo Hygiene (Including GitHub Actions)

  • Expert use of GitHub for collaboration, branching strategies, reviews, and automation
  • Version‑controlled test and automation infrastructure

Performance Test Infrastructure via Version Control

  • Designing and maintaining reusable, scalable performance test frameworks
  • CI‑integrated performance validation and regression detection

Observability, Metrics & Telemetry Intelligence

  • Instrumentation of systems and tests using metrics, logs, and traces
  • Data‑driven diagnosis of latency, throughput, and bottlenecks

General AI Literacy

  • Practical understanding of prompt design and structured prompting
  • Ability to work effectively with LLM APIs and AI tooling

Distributed Workflow Orchestration

  • Designing and operating distributed workflows (AI agents + tool calling)
  • Experience orchestrating complex automation pipelines

AI‑Driven Code & Test Scenario Generation

  • Using AI to generate test scenarios, code artifacts, and manifests
  • Focus on accelerating delivery while maintaining quality and governance

Cloud Architecture (AWS, Azure, or GCP)

  • Designing and operating cloud‑native SaaS systems
  • Familiarity with Infrastructure as Code (Terraform, CloudFormation, Helm)

CI/CD & DevOps‑Integrated Automation

  • Deep experience integrating automation into CI/CD pipelines
  • GitHub Actions, Azure DevOps, Jenkins, or equivalent

AI Governance & Evaluation

  • Applying guardrails, evaluation metrics, and quality controls to AI systems
  • Ensuring reliability, safety, and repeatability of AI outputs

Performance Modeling Expertise

  • Practical application of Little’s Law, USL, Amdahl’s Law
  • Queueing theory experience strongly preferred

Key Responsibilities (Condensed)

  • 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

Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or equivalent experience (Master’s preferred)
  • 8–10 years experience in software and performance engineering
  • 3+ years building cloud‑native SaaS systems
  • Demonstrated success leading technical initiatives and mentoring engineers
  • Experience delivering AI/ML or Generative AI solutions in production strongly preferred

Why Join Vertex

  • Work on mission‑critical, global SaaS systems where performance truly matters
  • Build AI‑driven engineering solutions with real, measurable impact
  • Operate with high ownership and influence, not ticket‑driven execution
  • Grow as a technical leader while shaping the future of intelligent performance automation

Our Core Values: 

Here are the Winning Way behaviors that all Vertex employees embrace every day: 

  • Own the Outcome: Commit to milestones and demonstrate unwavering support for team decisions. If you are unsure, ask! 
  • Work with Purpose: Foster a "We Can" mindset where results outweigh effort; everyone understands how their roles contribute to team outcomes. 
  • Act with Urgency: Adopt an agile mentality with a focus on quick iterations and resilience. 

  • Communicate with Clarity: Be clear, concise, and actionable. Embrace constructive feedback. 
  • Drive to Decision: Make decisions swiftly with defined deadlines and accountability.

Pay Transparency Statement:

US Base Salary Range: $138,800.00 - $180,400.00

Base pay offered to new hires may vary based upon factors including relevant industry and job-related skills and experience, geographic location, and business needs.* The range displayed does not encompass the full potential of the role, which allows for further growth and career progression.

In addition, as a part of our total compensation package, this role may be eligible for the Vertex Bonus Plan (VOB), a role-specific sales commission/bonus, and/or equity grants.

Learn more about Life at Vertex and connect with your recruiter for more details regarding Vertex's compensation and benefit programs.

*In no case will your pay fall below applicable local minimum wage requirements.

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