Applied AI Engineer

Job not on LinkedIn

🔥 7 minutes ago

🇺🇸 United States – Remote

💵 $150k - $175k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 19%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.Why this score:

• Just posted.
• Jobs at this company usually fill in 38 days.

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mpathic

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

🏥 Healthcare

💼 Consulting

🍽️ Food & Beverage

Healthcare • Consulting • Food & Beverage

mpathic is an AI-driven safety and analytics company that offers SaaS products and APIs to record, transcribe, analyze, and improve human–AI and human–human interactions in clinical, life‑science, and enterprise settings. Their offerings include speech-to-text transcription, PII redaction, behavior and checklist analytics, human-curated benchmarking datasets, red‑teaming expertise, and an Observing Agent API to add domain-informed guardrails for healthcare and medical agents. mpathic targets life sciences, clinical research organizations, healthcare providers, insurers, and HR/enterprise teams focused on empathy, safety, bias reduction, and compliance.

📋 Description

• Own, design, build, and run the LLM Gateway and the single path through which production services call model providers • Build logging, cost attribution, rate limiting, failover, and protected health information (PHI) controls • Remove direct provider API keys from services so model access occurs through the gateway • Maintain the approved catalog of models, providers, endpoints, and model features • Document data retention, BAA coverage, and version pinning, and record additions in decision records • Version prompts and model configurations alongside code • Run AI/ML evaluations as CI release gates with staged rollout and rollback • Provide self-service templates for sandbox and staging while gating production • Turn validated AI/ML prototypes, evaluation harnesses, and acceptance thresholds into scalable, observable production services • Advise on model cost, latency, and availability • Instrument LLM services with OpenTelemetry for latency, failures, token usage, cost, and output quality • Monitor evaluation drift, join on-call, and lead incident response for LLM-backed services • Produce audit evidence with Security and Compliance for SOC 2, ISO 27001, HIPAA, and FDA 21 CFR Part 11 • Collaborate with the CTO, platform engineering, ML, research, domain experts, sales, and delivery teams

🎯 Requirements

• 5+ years of backend software engineering, including multi-tenant SaaS services and APIs in production • Production experience building on commercial LLM APIs, including prompt management, structured outputs, and tool use • Hands-on experience designing evaluation pipelines for LLM output and wiring them into CI/CD as release gates • Strong Python • AWS, containers (ECS or similar), and infrastructure as code (Pulumi, Terraform, or CDK) • Observability tooling such as OpenTelemetry, Datadog, or similar • Experience with version control, feature flags, CI, and an issue tracker such as Linear • Working knowledge of application security, including secrets management, access control, and handling sensitive data • Preferred: experience in regulated domains such as healthcare or life sciences, including HIPAA, SOC 2, ISO 27001, or FDA 21 CFR Part 11 validated systems • Preferred: experience building an internal developer platform or paved road used by other teams • Preferred: experience with LLM-as-judge evaluation, red teaming, or conversational analytics • Preferred: experience with training or fine-tuning models from scratch

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