Simulation Engineering Manager (AI)

Location: New York City metropolitan area; in-person, five days a week in the office. Candidates must be located in the area or be open to relocation.

Salary: $280,000–$425,000 per year, plus equity.

Company

hirify.global builds simulations of human behavior using populations of AI agents to help companies and institutions test consequential decisions before committing to them.

What you will do

• Build, lead, and develop a high-performing team of Simulation Engineers responsible for production simulation quality.
• Own behavioral fidelity, calibration, reproducibility, latency, throughput, cost, reliability, debuggability, and safe operation.
• Turn research methods into production systems through architecture, typed contracts, evaluation gates, rollout workflows, observability, and rollback.
• Design simulation abstractions covering agents, populations, environments, state models, workflows, evaluation interfaces, and publication layers.
• Build evaluation harnesses, benchmarks, regression suites, diagnostics, and launch scorecards for simulation quality.
• Partner with Research, Evaluation, Product, Platform, Infrastructure, and Deployment teams to resolve failures and improve production operations.

Requirements

• Strong background as a software, machine-learning, or systems engineer, with continued hands-on work in code and architecture.
• Experience leading a small engineering team that shipped and operated an AI, ML, data, or distributed system in production.
• Ability to debug failures across data, prompts, orchestration, statistical assumptions, services, and user-facing outputs.
• Ability to turn underspecified research methods into deterministic, testable, observable, and efficient production systems.
• Experience designing evaluations and making tradeoffs among fidelity, calibration, latency, cost, reliability, maintainability, and iteration speed.
• Willingness to work in person in New York City five days a week.

Nice to have

• Experience with LLM applications, agentic systems, multi-agent frameworks, model orchestration, or inference-time computation.
• Experience with model evaluation, experimentation platforms, synthetic data, forecasting systems, or probabilistic models.
• Experience building simulation, scientific-computing, distributed-compute, workflow, or data-intensive systems at scale.
• Experience with reproducible experimentation, model and data versioning, ML observability, or safe model rollout.
• Research experience or close collaboration with research teams, including translating experimental methods into software.

Culture & Benefits

• Small, in-person team with high ownership, urgency, and intellectual honesty.
• Hands-on management focused on technical depth, clear interfaces, and strong engineering leadership.
• Comprehensive medical, vision, and dental coverage.
• Equity participation and competitive compensation within internal salary bands.
• Visa sponsorship and relocation support are available.