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Beacon AI
San Carlos, California, United States
Source: Beacon AI careers · View original posting
From Beacon AI's posting. “We” and “our” refer to the employer.
We’re a fast-moving team of aviators, engineers, and operators building an AI platform to make flying safer, more efficient, and more capable. Backed by top investors, we’ve secured a dozen Department of Defense contracts and partnered with major airlines to deliver mission-critical systems. We operate without silos or heavy processes. Small, focused teams own what they build, ship quickly, and learn fast, pushing the boundaries of how humans and AI work together in aviation.
You will ship LLM-powered product features end-to-end. That means designing retrieval and tool-calling flows, writing the services that run them, building evals and guardrails, and watching cost, latency, and quality in production. You’ll partner with the ML/infra teammates on embeddings, indexing, and model hosting, and with the product teammates on user experience and outcomes. We move fast, and we care about reliability in a safety-critical domain.
We’re hiring across levels. Senior engineers own features and services. Staff engineers own systems, standards, and cross-team technical direction.
You’ve put LLM features in front of users and improved them with data.
Comfortable writing production code, tests, and docs. You keep things simple and observable.
You understand embeddings, chunking, vector search tradeoffs, and function calling.
You design evals, define success metrics, and iterate based on evidence.
You track p95, hit SLAs, and reduce cost without hurting quality.
You explain tradeoffs and align partners across product, infra, and security.
Nice to have
Experience with Bedrock, OpenSearch Serverless, pgvector, Pinecone, or Weaviate.
Prompt versioning, guardrails, and provider routing in production.
Multimodal work with time series or video.
Familiarity with GPU inference, Triton, or TensorRT-LLM.
Aviation or other safety-critical domain exposure.
DevOps basics for CI/CD, IaC, and secure secrets handling.
Example problems you might tackle in month one
Transform an internal knowledge base into a low-latency RAG service, complete with explicit schemas and evaluations.
Add tool-calling to automate a repetitive cockpit or ops workflow with guardrails and audit trails.
Reduce the cost per request through improved chunking, caching, and prompt refactoring, while maintaining task success rates.
Work Location
This is a hybrid role based in San Carlos, CA, with 3+ days per week onsite and the option to work remotely on remaining days.
LAYIQ is an independent job-discovery service. This listing does not imply a partnership with or endorsement by the employer. Review the original posting for current details and availability.
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