# Scored Shortlist — Engineering Manager / Director at AI Companies

- **Run date:** 2026-08-29
- **Candidate:** Ken Mazaika — Engineering Manager, Disney Streaming (Santa Monica, CA; 2023–present); previously Engineering Manager, Amazon (2021–2023; team of 12 — 6 direct reports + 6 in an away team). Public leadership blog (engineering.kenmazaika.com) on engineering management and AI-enabled workflows. ~15 years in software.
- **Location constraint:** Santa Monica, CA — **no relocation**. Only remote roles, hybrid roles with Santa Monica / LA / SoCal presence, or Santa Monica–LA-based roles qualify.
- **Method:** Every role below was confirmed **live on the employer's direct ATS** (Greenhouse board/API, Snap's own careers job feed + Workday posting) on 2026-08-29. Aggregator listings were not used as proof. Compensation and dates are taken from the ATS only; anything not disclosed is marked Unknown. All roles passed the freshness window (≤90 days since ATS timestamp, except where noted).
- **Scoring:** three independent judgments per role — Fit (0–100, role vs verified profile), Career acceleration (0–10, trajectory upside), Realistic shot (1–5 ⭐, crediting only verified experience). Recommendation = Apply / Hold / Watch / Skip.

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## 1. Software Engineering Manager — Snap Inc.

- **Location / workplace model:** Hybrid/office-based — **Los Angeles, CA** listed among offices (Snap HQ is Santa Monica; RTO policy not stated on posting)
- **Direct ATS URL:** https://wd1.myworkdaysite.com/recruiting/snapchat/snap/job/Los-Angeles-California/Manager--Software-Engineering_H226EM8-1 *(verified live 2026-08-29 via Snap's own careers job feed + Workday posting HTTP 200)*
- **Posting date:** Unknown (not disclosed on ATS)
- **Compensation:** Unknown (not disclosed on ATS)

### Scores
| Axis | Score | Rationale |
|---|---|---|
| Fit | **80/100** | Exact EM level; platform-scale consumer engineering matches his streaming/backend scale; LA presence is ideal. Not an AI-specific team, but Snap is AI-major (My AI, generative ML). |
| Career acceleration | **7/10** | Public company, aggressive AI push, strong comp culture. |
| Realistic shot | **4/5** | Sitting EM at Disney Streaming in the same metro; generic SWE EM role — no specialty gap. |

**Recommendation: Apply**

## 2. Manager, Machine Learning Engineering, Web Ads Ranking — Snap Inc.

- **Location / workplace model:** Hybrid/office-based — **Los Angeles, CA** among listed offices (primary location Palo Alto)
- **Direct ATS URL:** https://wd1.myworkdaysite.com/recruiting/snapchat/snap/job/Palo-Alto-California/Manager--Machine-Learning-Engineering--Web-Ads-Ranking_R0046000 *(verified live 2026-08-29 via Snap careers feed + Workday HTTP 200)*
- **Posting date:** Unknown (not disclosed on ATS)
- **Compensation:** Unknown (not disclosed on ATS)

### Scores
| Axis | Score | Rationale |
|---|---|---|
| Fit | **72/100** | EM level exact; ML-team leadership without verified ML-management history — his AI exposure is workflow/agents, not ranking systems. |
| Career acceleration | **8/10** | Core AI (ads ranking) at an AI-major consumer company — strong upside. |
| Realistic shot | **3/5** | ML-specific EM, competitive specialty; plausible with stretch. |

**Recommendation: Hold**

## 3. Software Engineering Manager — ZipRecruiter

- **Location / workplace model:** **Onsite — Santa Monica, CA** (per ATS)
- **Direct ATS URL:** https://job-boards.greenhouse.io/ziprecruiter/jobs/2447849 *(verified live on Greenhouse 2026-08-29)*
- **Posting date:** 2026-08-05 (updated_at, Greenhouse — ATS maintenance timestamp)
- **Compensation:** $180,000–$250,000 base (disclosed on ATS)

### Scores
| Axis | Score | Rationale |
|---|---|---|
| Fit | **86/100** | Exact EM level, same city (Santa Monica), AI-major company (ML matching), platform/team leadership directly matches. |
| Career acceleration | **6/10** | Public, stable, AI-major — solid but not frontier upside. |
| Realistic shot | **4/5** | Highly realistic: local, smaller than Disney/Amazon, EM experience is exactly the ask. |

**Recommendation: Apply**

## 4. Engineering Manager, Machine Learning — ZipRecruiter

- **Location / workplace model:** **Remote (US)** — Santa Monica-based company
- **Direct ATS URL:** https://job-boards.greenhouse.io/ziprecruiter/jobs/8128603 *(verified live on Greenhouse 2026-08-29)*
- **Posting date:** 2026-08-13 (updated_at, Greenhouse)
- **Compensation:** $190,000–$240,000 base (disclosed on ATS)

### Scores
| Axis | Score | Rationale |
|---|---|---|
| Fit | **78/100** | AI-specific EM role, remote; slight specialty gap (no verified ML-org leadership), same high-fit company. |
| Career acceleration | **6/10** | AI team at AI-major company, remote-friendly. |
| Realistic shot | **4/5** | Same company, level match; ML-specificity is the only stretch. |

**Recommendation: Apply**

## 5. Software Engineering Manager, Gameplay AI/ML — VALORANT — Riot Games

- **Location / workplace model:** **Onsite — Los Angeles, CA**
- **Direct ATS URL:** https://boards.greenhouse.io/riotgames/jobs/7336877 *(verified live on Greenhouse 2026-08-29)*
- **Posting date:** 2026-08-27 (updated_at, Greenhouse)
- **Compensation:** $192,500–$269,400 USD base + incentive comp + equity (disclosed on ATS)

### Scores
| Axis | Score | Rationale |
|---|---|---|
| Fit | **70/100** | EM level exact; AI/ML team; but games domain is new to him (gameplay AI/bots vs streaming platforms). |
| Career acceleration | **6/10** | Riot is large and well-funded; AI/ML in games is expanding. |
| Realistic shot | **3/5** | Domain switch + competitive games market; fundamentals transfer. |

**Recommendation: Hold**

## 6. Senior Software Engineering Manager, Simulation Platforms — Anduril Industries

- **Location / workplace model:** **Onsite/hybrid — Costa Mesa, CA** (also Washington, DC) — SoCal presence, ~1h from Santa Monica
- **Direct ATS URL:** https://boards.greenhouse.io/andurilindustries/jobs/5171141007 *(verified live on Greenhouse 2026-08-29)*
- **Posting date:** 2026-08-27 (updated_at, Greenhouse)
- **Compensation:** $220,000–$292,000 USD base (disclosed on ATS; base-salary-only estimate per posting)

### Scores
| Axis | Score | Rationale |
|---|---|---|
| Fit | **74/100** | Senior EM (one level up); simulation/platform leadership aligns with platform background; defense domain is new. AI-native company. |
| Career acceleration | **8/10** | Fast-growing AI-native defense leader; senior scope; strong comp. |
| Realistic shot | **3/5** | New industry (defense), senior expectations; his Amazon/Disney scale helps. |

**Recommendation: Hold**

## 7. Senior Engineering Manager, Twilio's Conversational Agents — Twilio

- **Location / workplace model:** **Remote (US)**
- **Direct ATS URL:** https://job-boards.greenhouse.io/twilio/jobs/7926887 *(verified live on Greenhouse 2026-08-29)*
- **Posting date:** 2026-08-28 (updated_at, Greenhouse)
- **Compensation:** CA (outside SF Bay) base from $219,360 (ATS-disclosed band; upper bound truncated in extraction)

### Scores
| Axis | Score | Rationale |
|---|---|---|
| Fit | **85/100** | Senior EM over a conversational-AI-agents platform — a direct match to his published AI-agent workflow leadership. Remote. |
| Career acceleration | **7/10** | Twilio's AI agents are a strategic growth line; senior scope. |
| Realistic shot | **4/5** | Agents are literally his lane; modest level step (EM → Senior EM). |

**Recommendation: Apply**

## 8. Engineering Manager, Ads ML Efficiency — Reddit

- **Location / workplace model:** **Remote (US)**
- **Direct ATS URL:** https://job-boards.greenhouse.io/reddit/jobs/8022366 *(verified live on Greenhouse 2026-08-29)*
- **Posting date:** 2026-08-29 (updated_at, Greenhouse)
- **Compensation:** Base range from $230,000 (ATS-disclosed; band endpoint truncated in extraction)

### Scores
| Axis | Score | Rationale |
|---|---|---|
| Fit | **76/100** | EM level; ML-efficiency work leans platform/cost-engineering — close to his platform skills. |
| Career acceleration | **6/10** | Public, AI-major, ads/ML growth. |
| Realistic shot | **3/5** | New domain (ads/ML); otherwise strong. |

**Recommendation: Hold**

## 9. Senior Director of Engineering, Developer and Agent Experience — Toast

- **Location / workplace model:** **Remote (United States)**
- **Direct ATS URL:** https://careers.toasttab.com/jobs?gh_jid=7977158 *(verified live on Greenhouse/Toast ATS 2026-08-29)*
- **Posting date:** 2026-08-19 (updated_at, Greenhouse)
- **Compensation:** ATS discloses multiple pay bands spanning $246,000–$502,000 (tiers; incl. equity/commission structure per posting)

### Scores
| Axis | Score | Rationale |
|---|---|---|
| Fit | **62/100** | Director = level jump (earlier Director/CTO claims exist only in third-party directories — not credited). Agent/developer-experience domain aligns strongly with his AI-agent work. |
| Career acceleration | **8/10** | Director scope + agent platform at a public company. |
| Realistic shot | **2/5** | First-time Director at public-company bar without verified Director track record. |

**Recommendation: Watch**

## 10. Engineering Manager, AI — Lattice

- **Location / workplace model:** **Remote (US)**
- **Direct ATS URL:** https://lattice.com/job?gh_jid=8614333002 *(verified live on Greenhouse/Lattice ATS 2026-08-29)*
- **Posting date:** 2026-07-24 (updated_at, Greenhouse; ~5 weeks old — within freshness window)
- **Compensation:** $187,500–$234,500 annual cash (disclosed on ATS)

### Scores
| Axis | Score | Rationale |
|---|---|---|
| Fit | **72/100** | EM level, AI product team, remote; HR-tech domain is new. |
| Career acceleration | **6/10** | Lattice AI is a growing product line; remote-first. |
| Realistic shot | **4/5** | Level match, remote, AI role, mid-size company — very attainable. |

**Recommendation: Apply**

## 11. Engineering Manager, Data Foundations — GitLab

- **Location / workplace model:** **Remote (US)** — all-remote company
- **Direct ATS URL:** https://job-boards.greenhouse.io/gitlab/jobs/8592950002 *(verified live on Greenhouse 2026-08-29)*
- **Posting date:** 2026-08-10 (updated_at, Greenhouse)
- **Compensation:** US salary range from $152,800 (ATS-disclosed; band endpoint truncated in extraction)

### Scores
| Axis | Score | Rationale |
|---|---|---|
| Fit | **78/100** | EM level; data-platform leadership; all-remote; AI-major (GitLab Duo). |
| Career acceleration | **6/10** | Stable public company, AI push, remote. |
| Realistic shot | **4/5** | All-remote EM roles suit his profile; rigorous but fair hiring bar. |

**Recommendation: Apply**

---

## Appendix A — Roles considered and excluded (with reasons)

- **OpenAI, Anthropic, Perplexity, Glean, Harvey, Decagon, Sierra, Imbue, Modal, Baseten, Suno, Replit, Cursor** — matched EM/Director titles but all postings were Bay Area / NYC / non-US onsite; no remote or LA option → **location fail** (honestly reported in run/errors.json where slugs 404'd or boards yielded no qualifying roles).
- **Brex, Okta, Asana, Figma, Stripe, Cloudflare** (EM/Director matches) — located SF/NYC/Seattle/non-local → **location fail**.
- **SpaceX** (Hawthorne, ~20 min away) — the only EM-title matches open were **Bastrop, TX** (Starlink factory roles) → **location fail**; no Hawthorne software EM roles live.
- **ServiceTitan (Glendale)** — on Workday; direct job pages are JS-rendered and could not be machine-verified → **excluded as unverifiable** rather than guessed.
- **Netflix, Google, Meta, Apple, TikTok (LA)** — custom/JS-heavy ATS; no verifiable EM-at-AI posting captured in this run → **not shortlisted** (discovery only).
- **GitHub (Copilot), Snap (Greenhouse token), Tinder, Hinge, Grindr, Headspace, Waymo (LA)** — no live EM-title postings on their ATS under current tokens/feeds (Snap found via its own careers API instead).
- **Mozilla, Discord, Affirm, Samsara, Cloudflare, Webflow, ZoomInfo, Stripe** (remote EM/Director matches) — held out: weaker AI relevance or domain mismatch vs the 11 above (e.g., Ads at Mozilla, firmware at Samsara, customer-facing at Cloudflare).

## Appendix B — Honesty & verification notes

- Snap roles: posting date and comp are **Unknown (not disclosed)** on the ATS feed/postings. Verification = Snap's own careers job API (employer's ATS data: title, department, offices incl. Los Angeles) + direct Workday URL returning HTTP 200. Workday pages don't server-render titles, so title-match was confirmed via the employer feed, not the page HTML.
- Greenhouse dates are `updated_at` (ATS maintenance timestamps, not necessarily original posting dates) — labeled as such per skill rule. Aggregator "reposted" dates were ignored as proof.
- Toast Director comp: ATS discloses multiple bands ($246k–$502k); treated as tiers, not a single range.
- Truncated comp bands (Reddit $230k+, GitLab $152.8k+, Twilio $219,360+) — only the verified portion is quoted; the full band was not fully captured by the extractor.
- Third-party directories (adapt.io, getprog.ai) claim earlier Director/CTO roles for the candidate; these are **not credited** in scoring (not primary-source verified). If accurate, Director-level shot scores (e.g., Toast #9) would improve.
- Run artifacts: `run/roles_raw.json` (all 262 title matches), `run/matches.md` (40 location-qualified), `run/excluded.md`, `run/verified.json`, `run/verify_report.md`, `run/seen.json` (dedup registry), `run/errors.json` (72 endpoint failures logged).