<?xml version="1.0" encoding="UTF-8"?>
<source>
  <publisher>ANDYGROVE.SYSTEMS — High Output Operations for Human + Agent Teams</publisher>
  <publisherurl>https://andygrove.systems</publisherurl>
  <lastBuildDate>Sun, 15 Nov 2026 13:30:00 GMT</lastBuildDate>
  <job>
    <title><![CDATA[Industrial Engineer & Multi-Agent Queueing / Bottleneck Architect (Part-Time Remote R&D Pod)]]></title>
    <date><![CDATA[2026-11-15]]></date>
    <referencenumber><![CDATA[GROVE-IE-QUEUE-01]]></referencenumber>
    <url><![CDATA[https://baserow.io/form/5dGFgfNPjhbG9qpSw8A3yGNK72vJQkGmkr__j_qmyn8?prefill_Source+Site=andygrove.systems&hide_Source+Site]]></url>
    <company><![CDATA[ANDYGROVE.SYSTEMS]]></company>
    <city><![CDATA[Remote]]></city>
    <country><![CDATA[Worldwide]]></country>
    <jobtype><![CDATA[Part-Time Remote R&D Pod (10–25 hrs/wk)]]></jobtype>
    <salary><![CDATA[$25–$45 / hr USD]]></salary>
    <education><![CDATA[Industrial Engineering, Operations Research, BizOps / Program Management, or Process & Quality Engineering]]></education>
    <description><![CDATA[Model multi-agent and human-in-the-loop workflows as stochastic Jackson/G-G-m production lines with visit ratios v_i. Identify limiting steps, size CONWIP buffers, eliminate variance-wedge congestion, and cut p95 cycle time. Canonical Law: L = λ_0 W_sys,   Θ_sys = min_i (N_i μ_i / v_i). Skills: Industrial Engineering, Queueing Theory (L = λW), Bottleneck Analysis, Discrete-Event Simulation, Python / SQL. Apply via https://baserow.io/form/5dGFgfNPjhbG9qpSw8A3yGNK72vJQkGmkr__j_qmyn8?prefill_Source+Site=andygrove.systems&hide_Source+Site. Independent platform; not affiliated with Intel Corporation or the Grove family.]]></description>
  </job>
  <job>
    <title><![CDATA[Process & Quality Engineer — Task-Relevant Maturity (TRM) & Eval Gates (Part-Time Remote R&D Pod)]]></title>
    <date><![CDATA[2026-11-15]]></date>
    <referencenumber><![CDATA[GROVE-TRM-EVAL-02]]></referencenumber>
    <url><![CDATA[https://baserow.io/form/5dGFgfNPjhbG9qpSw8A3yGNK72vJQkGmkr__j_qmyn8?prefill_Source+Site=andygrove.systems&hide_Source+Site]]></url>
    <company><![CDATA[ANDYGROVE.SYSTEMS]]></company>
    <city><![CDATA[Remote]]></city>
    <country><![CDATA[Worldwide]]></country>
    <jobtype><![CDATA[Part-Time Remote R&D Pod (10–25 hrs/wk)]]></jobtype>
    <salary><![CDATA[$20–$45 / hr USD]]></salary>
    <education><![CDATA[Industrial Engineering, Operations Research, BizOps / Program Management, or Process & Quality Engineering]]></education>
    <description><![CDATA[Design statistical process control (SPC) charts, variable lot-sampling plans, deterministic pre-bottleneck eval harnesses, and Wilson-calibrated Task-Relevant Maturity gates governing agent autonomy. Canonical Law: TRM_{1−α}(A, τ) = WilsonLowerBound(p̂_eval, n, z_{1−α}). Skills: Process & Quality Engineering, Statistical Process Control, Wilson TRM Bounds, Six Sigma / Acceptance Sampling, Guardrail Telemetry. Apply via https://baserow.io/form/5dGFgfNPjhbG9qpSw8A3yGNK72vJQkGmkr__j_qmyn8?prefill_Source+Site=andygrove.systems&hide_Source+Site. Independent platform; not affiliated with Intel Corporation or the Grove family.]]></description>
  </job>
  <job>
    <title><![CDATA[Operations Researcher — Human + Agent Handoff & Routing Optimization (Part-Time Remote R&D Pod)]]></title>
    <date><![CDATA[2026-11-15]]></date>
    <referencenumber><![CDATA[GROVE-OR-HANDOFF-03]]></referencenumber>
    <url><![CDATA[https://baserow.io/form/5dGFgfNPjhbG9qpSw8A3yGNK72vJQkGmkr__j_qmyn8?prefill_Source+Site=andygrove.systems&hide_Source+Site]]></url>
    <company><![CDATA[ANDYGROVE.SYSTEMS]]></company>
    <city><![CDATA[Remote]]></city>
    <country><![CDATA[Worldwide]]></country>
    <jobtype><![CDATA[Part-Time Remote R&D Pod (10–25 hrs/wk)]]></jobtype>
    <salary><![CDATA[$25–$45 / hr USD]]></salary>
    <education><![CDATA[Industrial Engineering, Operations Research, BizOps / Program Management, or Process & Quality Engineering]]></education>
    <description><![CDATA[Formulate dynamic triage, token-budget allocation, and confidence-aware human-agent handoff policies using Markov decision processes, queueing networks, and integer optimization. Canonical Law: min_{x, π} ∑ c_i x_i + c_esc P(escape | π)   s.t.   ρ_i < 1. Skills: Operations Research, Human + Agent Handoffs, Stochastic Networks, MIP / Dynamic Routing, Cost-Throughput Modeling. Apply via https://baserow.io/form/5dGFgfNPjhbG9qpSw8A3yGNK72vJQkGmkr__j_qmyn8?prefill_Source+Site=andygrove.systems&hide_Source+Site. Independent platform; not affiliated with Intel Corporation or the Grove family.]]></description>
  </job>
  <job>
    <title><![CDATA[BizOps & Technical Program Manager — Leading Indicators & OKR Systems (Part-Time Remote R&D Pod)]]></title>
    <date><![CDATA[2026-11-15]]></date>
    <referencenumber><![CDATA[GROVE-BIZOPS-OKR-04]]></referencenumber>
    <url><![CDATA[https://baserow.io/form/5dGFgfNPjhbG9qpSw8A3yGNK72vJQkGmkr__j_qmyn8?prefill_Source+Site=andygrove.systems&hide_Source+Site]]></url>
    <company><![CDATA[ANDYGROVE.SYSTEMS]]></company>
    <city><![CDATA[Remote]]></city>
    <country><![CDATA[Worldwide]]></country>
    <jobtype><![CDATA[Part-Time Remote R&D Pod (10–25 hrs/wk)]]></jobtype>
    <salary><![CDATA[$20–$45 / hr USD]]></salary>
    <education><![CDATA[Industrial Engineering, Operations Research, BizOps / Program Management, or Process & Quality Engineering]]></education>
    <description><![CDATA[Partner with COO offices to replace lagging vanity reports with paired leading-indicator dashboards, staggered forecast tables, operational review cadences, and high-output OKR trees. Canonical Law: Paired Telemetry: Leading(throughput, linearity) × Counter-Indicator(quality, rework). Skills: BizOps & Program Management, Leading Indicators, OKR Systems Design, COO Telemetry Dashboards, Cross-Functional Process Design. Apply via https://baserow.io/form/5dGFgfNPjhbG9qpSw8A3yGNK72vJQkGmkr__j_qmyn8?prefill_Source+Site=andygrove.systems&hide_Source+Site. Independent platform; not affiliated with Intel Corporation or the Grove family.]]></description>
  </job>
</source>