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Why this grade This listing scored 58/100, which is a C. It lost the most ground on pay transparency. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Remote clarity 15 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Pay transparency 12 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
- Freshness 8 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Role specificity 3 / 10 Whether the listing is tagged well enough to tell what the role actually is.
-5 Ghost-job penalty — Deducted for signals that this posting may not be a real, currently-open role — staleness, repeated relisting, or talent-pool language.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
This listing does not state a salary
$163k – $276k
That is the middle half of what comparable roles paid on this board over the last 90 days — 31 listings that did publish a figure, median $179k. It is not this employer's offer, and we have no idea what they pay. It is only what the rest of the market advertised.
hn-hiring
target bonus
Republic Services is the second largest environmental services companies in North America — ~40K employees, thousands of trucks, hundreds of facilities, and a mountain of operational data that has never had an AI layer on top of it. We have a backlog of hundreds of Agentic AI ideas that we need to deliver and a foundation of ontologies, evaluations, guardrails, etc... that we need to build.
We're hiring a Staff Engineer now to be the first hire and plan to expand the team aggressively. You will own that platform end to end, not manage the people.
What you'll work on
- Agent orchestration: tool calling, planner/executor and multi-agent patterns, MCP/A2A integrations with enterprise systems
- Making enterprise context reliably available at inference time — retrieval, memory, hybrid search, reranking, access controls
- LLMOps that isn't hand-wavy: evals and golden datasets, prompt/agent versioning, tracing, token and cost budgets, CI/CD for agents
- Safety in a regulated enterprise: prompt injection, data exfiltration, PII handling, human-in-the-loop, audit logging
You should have
- 7–10+ years building and scaling production systems, with recent, hands-on GenAI/agentic work in production (not just demos)
- Shipped agents or LLM pipelines at scale
- Solid data chops — vector stores, chunking, hybrid search, knowing when retrieval is the wrong answer
- Cloud experience (we're primarily AWS / Bedrock); comfortable with both containers and serverless
- Track record of technical leadership and mentoring without needing a manager title
Nice to have: LangGraph / Semantic Kernel / PydanticAI, GraphRAG, knowledge graphs, LangFuse/LangSmith, multimodal.
Comp & benefits: $175k is our midpoint for salary + 20% annual target bonus, 401(k) with company match, ESPP, medical/dental/vision, PTO. Remote eligible, prefer AZ timezones +/-1. Not sponsorship eligible.
Why you should want to work here: We build cool stuff
email me ([email protected]) directly with the most interesting agent you've shipped.
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Where this listing came from
- 02 Sep 2026 Hacker News first sighting
Seen on 1 board over 28 days.