Staff Software Engineer – AI-Native Development

SimSpace Corporation

2d•$185,000 - $260,000

About The Position

SimSpace is hiring a Staff Software Engineer to provide hands-on technical leadership and help define how engineering teams build software in the age of AI. The role combines direct software development with technical direction, cross-team project leadership, and the creation of standards and workflows for AI-native development. It is an individual-contributor role, not a people-management position, and partners closely with an Engineering Manager as well as Product Managers, UX Designers, QA, platform teams, and engineers across the organization. The engineer will model spec-driven development with AI agents, from writing specifications, plans, and acceptance criteria through directing implementation and reviewing and verifying AI-generated code. They will lead complex initiatives from problem framing through architecture, delivery, and rollout; establish practical standards and materials that help teams adopt effective AI workflows; and improve CI/CD testing, quality practices, and delivery speed. The role calls for substantial ownership of technical direction and outcomes, with an emphasis on incremental delivery, trusted feedback loops, and collaboration across teams. SimSpace develops cyber environments where organizations train, test, and operationalize cyber capabilities. Its technology stack includes Codex, TypeScript, React, Kotlin, Git/GitHub, Docker, Kubernetes, ArgoCD, and Playwright. The listed base salary range is $180,000–$260,000, with potential annual bonuses tied to company performance and individual contributions.

Requirements

At least 8 years of professional software engineering experience.
A track record of leading technical projects end to end across teams.
Daily use of AI coding agents, with the ability to direct them effectively and demonstrate how they have changed delivery practices.
Familiarity with spec-driven development using AI agents, including writing specifications, plans, and acceptance criteria that agents implement and reviewers verify against.
Demonstrated ability to establish and raise engineering standards adopted by multiple teams.
Proven cross-organization collaboration and ability to complete shared initiatives with Product, QA, platform teams, and engineers on other teams.
Deep, hands-on software engineering expertise sufficient to set architectural direction, make difficult technical decisions, and critically review AI-generated code.
Strong written and verbal communication skills, including ability to explain trade-offs to non-engineering partners.

Nice To Haves

Experience building headless coding agents that run without an IDE or a human at the keyboard, such as in CI/CD pipelines, on event triggers, or as background workers.
Experience improving end-to-end testing in CI/CD pipelines so test suites are fast, reliable, and trusted enough to gate releases.
A track record of enabling small batches, short feedback loops, and frequent releases without lowering quality.
Experience with practices that make delivery speed safe, such as trunk-based development, feature flags, progressive delivery, and fast rollback.
Experience with TypeScript, React, or Kotlin is identified as ideal.

Responsibilities

Define and model how teams specify work, direct AI agents, and review, test, and own AI-generated code.
Champion spec-driven development by writing clear specifications, plans, and acceptance criteria and helping teams adopt the practice.
Develop and maintain practical standards, playbooks, templates, documentation, examples, and internal talks for AI-native workflows.
Evaluate emerging AI tools and workflows, adopting those that improve delivery and retiring those that do not.
Lead complex cross-team initiatives from problem framing and specification through architecture, delivery, and rollout.
Build alignment across Product, Engineering, QA, and platform teams, and resolve technical dependencies.
Identify stalled or drifting work, unblock it, make technical decisions, and communicate progress, risks, and trade-offs to stakeholders.
Improve end-to-end testing maturity in CI/CD so AI-assisted delivery remains high quality.
Help teams deliver small changes frequently, supported by fast feedback loops and trusted quality gates.
Identify opportunities for AI agents, including headless agents in CI/CD or triggered by events, to reduce toil, and build or adopt them with appropriate guardrails.
Set and uphold standards for code health, testing, and documentation, including standards for AI-generated code, and model them in code reviews.
Own the team's technical direction and execution in partnership with the Engineering Manager.
Break large efforts into incremental deliverables, sequence work, and support predictable delivery.
Raise risks early with proposed paths forward.
Mentor engineers through code reviews, pairing, and design walkthroughs.

Benefits

Competitive base salary range of $180,000–$260,000 and opportunity for annual performance-related bonuses.
Comprehensive medical, dental, and vision benefits, plus savings plans; coverage starts on day one.
Company-paid counseling, coaching, and family resources through Spring Health.
401(k) retirement savings plan with company match.
Unlimited vacation and dedicated health and wellness days, with flexible solutions for work-life needs.
Paid parental leave.
Equity stock options at hire, with annual performance-based grants.
Employee referral rewards of $1,500–$3,500 for each qualified hire.
Full- and partial-subsidized Peloton membership plans and equipment discounts.
LinkedIn Learning membership.
Monthly reimbursements for meaningful connections with teammates through the SocialSpace Community.
Legal plan coverage, pet insurance, and wellness reimbursements.