Senior ML / AI Engineer

Nonstop Administration & Insurance Services

. Design and ship agentic systems using dynamic tool-calling agents, structured Pydantic outputs, governed tool catalogs, per-step verification, grounding checks, LLM-as-judge, human-in-the-loop, and bounded auditable loops .

Posted 9/15/2026full-timeRemote • United StatesSenior💰 $150,000 - $210,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and shipping ML/AI systems in production, with a strong focus on LLM applications, MLOps governance, and cloud infrastructure management. Proficient in Python programming, system optimization, and ensuring reliability and compliance in regulated environments.

Highest-signal resume keywords

ML/AI Systems DevelopmentPython ProgrammingMLOps on AWSLLM Application ExperienceRegulated Data Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ML/AI SystemsPythonLLM Application WorkPromptingEmbeddingsRAGKubernetesTerraformPostgresMongoDB

Soft Skills

Clear Written CommunicationJudgment Under Ambiguity

Tools & Technologies

EKSOpenTelemetryPrometheusGrafanaReactTypeScriptVLLMSQSCognitoAmazon Bedrock

Industry Keywords

HIPAASOC 2ISO 27001PHIPIIAudit TrailsHealthcareInsuranceClaimsX12 835

Tech Stack

Tools & technologies

AWSCloudGrafanaKubernetesMongoDBPostgresPrometheusPythonReactTerraformTypeScript

About the role

Key responsibilities & impact

Design and ship agentic systems using dynamic tool-calling agents, structured Pydantic outputs, governed tool catalogs, per-step verification, grounding checks, LLM-as-judge, human-in-the-loop, and bounded auditable loops
Build the RAG layer, including document ingestion, chunking, embeddings, hybrid retrieval, reranking, access scoping, and injection/poisoning defenses
Operate self-hosted inference at scale with vLLM and embedding/rerank services on EKS GPU nodes
Optimize inference throughput using continuous batching, prefix caching, quantization, and KV-cache tuning
Enforce fair-share concurrency across tenants
Own the MLOps and governance plane, including offline evaluation harnesses, golden sets, quality scoring, canary/gray releases, auto-rollback, cost/budget governance, and observability
Make systems production-safe through durable state, circuit breakers, retries, PHI-safe logging/redaction, RBAC, fail-closed defaults, and horizontal AWS scalability via Terraform
Extend the platform to new domains from problem framing through governed, evaluated, deployed services
Mentor engineers on building initiatives on the shared platform foundation
Maintain clean, typed, tested code and participate in thoughtful design reviews
Balance autonomy and determinism for high-stakes tasks

Requirements

What you’ll need

5+ years building and shipping ML/AI systems in production, including hands-on LLM application work in the last 1–2 years
Strong Python (typed, tested, production-grade) and solid software-engineering fundamentals
Comfortable across an async web service, a data layer, and infrastructure
Practical depth in prompting, structured/function-calling outputs, RAG, embeddings, vector search, retrieval quality, agent/tool-use loops, grounding, hallucination control, eval sets, and guardrails
Cloud and MLOps experience on AWS or equivalent, including containers, Kubernetes, Terraform, CI/CD, observability, and model-serving cost/performance tuning
Track record of owning reliability, including state durability, failure handling, scaling, and debugging production incidents
Clear written communication and judgment under ambiguity
Experience self-hosting/optimizing open-weight models such as vLLM or TGI on GPUs
Experience with embeddings/rerank serving, such as bge or Infinity
Experience with LangGraph, LangChain, or comparable agent frameworks and multi-agent orchestration
Regulated-data experience with HIPAA, SOC 2, ISO 27001, PHI/PII handling, RBAC, and audit trails
pgvector/Postgres, MongoDB/DocumentDB, SQS, and Cognito/OIDC
OpenTelemetry, Prometheus/Grafana, and frontend development with React/TypeScript
Amazon Bedrock or a multi-provider abstraction
On-premises or air-gapped deployment experience
Healthcare/insurance/claims domain experience, including X12 835, EOB, or benefits, is a strong plus
Must be authorized to work for any employer in the United States; this job does not offer visa sponsorship

Benefits

Comp & perks

100% coverage of medical, dental and vision benefits for employees and dependents
401k match up to 4%