Software Engineer - Traffic Capacity & Performance

Meta•Menlo Park, CA

2d•$183,997 - $257,000

About The Position

Meta's Traffic Capacity & Performance team determines how much capacity to build for the edge network and where to build it. The team plans for traffic flowing from edge sites and caches to people, as well as Meta services and AI agents reaching sites across the internet. It sizes capacity to withstand failures and demand spikes, tests resilience by intentionally draining sites during peak periods, and helps applications and services reduce demand when capacity is constrained. The Software Engineer will develop large-scale traffic simulations, constrained-optimization solvers, forecasting systems, and agentic planning tools. The role includes planning capacity for internet access through browsers, proxies, and caches; modeling failure risks and demand uncertainty; validating models against production behavior; and translating plans into risk and cost trade-offs. The engineer will lead technical work across teams, mentor engineers, participate in design reviews, and operate production systems, including on-call responsibilities.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
At least 7 years of software development experience in industry, or a PhD with at least 4 years of experience.
Proficiency in Python and at least one of C++, Java, Go, or Rust.
Experience building and operating production systems or large-scale data pipelines.
Experience in at least one of large-scale simulation, mathematical optimization, or forecasting systems.
Experience leading technical work that spans multiple teams.

Nice To Haves

Experience running large scenario sweeps on distributed compute, such as Spark or Presto.
Experience building discrete-event, flow-level, or Monte Carlo simulations and validating them against production.
Experience applying LLM-based agents to production workflows, including evaluations.
Experience with mixed-integer or linear programming and solvers such as Gurobi, CPLEX, OR-Tools, or HiGHS, or with large-scale heuristic search.
Experience with network capacity planning, traffic engineering, content delivery networks, load balancing, or forward proxies at scale.
Experience with reliability engineering, including failure modeling, failure-domain analysis, disaster recovery, or chaos testing.
Experience with probabilistic, driver-based forecasting, including launches and events.
Advanced degree in operations research, computer science, electrical engineering, applied mathematics, or a related field.

Responsibilities

Build and extend large-scale simulations of global traffic placement across edge sites as demand grows and sites, peering links, or backbone paths fail; run thousands of scenarios efficiently.
Collaborate with the load-balancing team to improve simulation fidelity and performance, and validate results against production behavior and live failure tests.
Formulate capacity planning as constrained optimization across compute, peering, and caches, accounting for space, power, supply, latency, and failure constraints; build and tune solvers.
Plan capacity for the browsers, proxies, and caches Meta services and AI agents use to access the internet, and identify emerging bottlenecks as demand grows.
Build production forecasts of peak demand by region and product, driven by product changes and events; quantify uncertainty and measure forecast accuracy against actual demand.
Model correlated and cascading failures and their impact; size buffers for failures and demand surges, and present risk and cost trade-offs for leadership decisions.
Build agentic planning systems that continuously rerun forecasts and plans, detect drift, explain changes, and propose actions, with evaluations and guardrails.
Lead technical direction across teams, mentor engineers, and represent capacity engineering in cross-team design reviews.
Operate production systems built by the team, including participating in on-call.