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Senior AI Engineer

Remote US

About Ethos

Ethos is a leading life insurance technology company on a mission to protect families by democratizing access to life insurance and empowering agents at scale. With its robust three-sided technology platform, Ethos is transforming the life insurance experience for consumers, agents, and carriers alike. Ethos offers instant, accessible products and a seamless online process that requires no medical exams and just a few health questions; it eliminates traditional barriers, making it easier than ever for everyone to protect their families. Ethos is redefining how life insurance is bought, sold, and underwritten.

About the Role

We’re building several LLM-powered copilots across critical workflows (e.g., underwriting productivity, agent enablement, customer support, operations/compliance, fraud). We need an AI engineer to own the LLM + retrieval + context layer that makes these copilots accurate, auditable, fast, and cost-efficient. 

Typical stack: Python/FastAPI, Postgres + vector (pgvector/Pinecone/Weaviate), OpenSearch, optional graph DB, Kubernetes + GPUs, OTEL/Datadog

Duties and Responsibilities:

  • Production RAG: indexing, retrieval, hybrid search, reranking, query rewriting, grounding, citations
  • Context Graph: entity resolution + linking + provenance; graph + vector retrieval; supports multi-hop context
  • LLM orchestration: tool/function calling, structured outputs, routing across model tiers, failure modes
  • GPU/inference cost optimization: batching, caching/KV reuse, quantization, autoscaling; optimize $/session + latency
  • Safety + compliance: PII/PHI handling, redaction, audit logs, deterministic replay, hallucination mitigation
  • LLMOps: eval harness (golden sets, regression, adversarial), monitoring for quality/cost/drift
  • Design/ship the end-to-end pipeline: retrieve → assemble context → generate → cite → log/monitor
  • Improve quality and trust via evaluation, feedback loops, and clear evidence-backed outputs
  • Partner with product, security, and domain teams; write crisp design docs; raise engineering bar
  • Ship RAG v1 with citations + measurable quality metrics
  • Deliver Context Graph v1 that improves retrieval on real copilot tasks
  • Reduce cost/latency with a concrete inference optimization plan shipped to prod

Qualifications and Skills:

  • 7+ years building production systems; 2+ years hands-on LLMs/RAG
  • Proven RAG experience (embeddings, vector DBs, hybrid search, reranking, eval)
  • Strong backend/distributed systems + observability
  • Track record shipping in high-stakes environments with auditability/correctness
  • Knowledge graph / entity resolution / provenance systems
  • GPU inference optimization (vLLM/TGI/TensorRT-LLM, quantization AWQ/GPTQ, batching)
  • Regulated domain experience (insurance/fintech/healthcare)

#LI-Remote #LI-MK1

The US national base salary range for this full-time position is $146,000 - $236,000. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. 

Please note that the compensation details listed in US role postings reflect the base salary only and do not include applicable bonus, equity, or benefits. 

You can find further details of our US benefits at https://www.ethoslife.com/careers/

Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. At Ethos we are dedicated to building a diverse, inclusive and authentic workplace.

We are an equal opportunity employer.. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Pursuant to the SF Fair Chance Ordinance, we will consider employment for qualified applicants with arrests and conviction records.

To learn more about what information we collect and how it may be used, please refer to our California Candidate Privacy Notice.

Recruitment Notice: Please be aware of recruitment scams. All legitimate communication from our team will only come from email addresses ending in @ethos.com or @getethos.com.
We will never ask for payment, banking details, or sensitive personal information during the hiring process. If you are contacted by someone claiming to represent us from a different email address, please treat it as fraudulent.

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