13 дней назад
AI Engineer
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Engineer (Python/LLM): Building and operating production AI services, retrieval pipelines, and integrations for internal and customer-facing benefit technology with an accent on secure LLM orchestration, multi-tenant data isolation, and regulated-industry compliance. Focus on designing reliable retrieval-augmented features, evaluating prompts and models, protecting PHI, and operating observable AI systems in production.
Location: Remote, with preference given to East Coast candidates
Company
builds benefit technology products and internal tooling with AI-enabled automation capabilities.
What you will do
- Build production-quality Python services, pipelines, and integrations using LLMs and retrieval.
- Integrate LLM APIs into existing systems, applying guidance for model selection, cost management, and failure handling.
- Develop retrieval- and LLM-backed features for lakehouse and analytics systems, including semantic search, summarization, anomaly narration, and contextual guidance.
- Create prompt libraries, evaluation frameworks, reference implementations, and reusable AI components.
- Implement AI-specific security and compliance controls, including PHI protection, audit logging, data residency, prompt-injection defenses, DLP, access governance, and secrets handling.
- Participate in design reviews, incident response, on-call operations, observability, documentation, and production metrics reporting.
Requirements
- 3–5 years of software engineering experience, including at least one year working on AI- or ML-backed systems and experience contributing to an LLM-backed production system.
- Strong Python skills for production services, data pipelines, and integrations.
- Working knowledge of programmatic LLM orchestration, evaluation frameworks, agents, and tool-using systems.
- Experience building retrieval-augmented systems and familiarity with Databricks and Azure or AWS.
- Familiarity with CI/CD, infrastructure-as-code, and MLOps practices for AI/ML systems.
- Experience with generative AI tools such as Claude and Copilot, plus a bachelor’s or master’s degree in a related field.
Nice to have
- Production experience in a regulated industry with familiarity with HIPAA, SOC 2, or NIST.
- Experience with multi-tenant SaaS data isolation and identity and access patterns for B2B platforms.
Culture & Benefits
- Collaborative work with engineering, product, customer success, security, data, operations, and architecture teams.
- Participation in technical direction, build-versus-buy decisions, and the roadmap for customer-facing AI capabilities.
- Opportunities to improve engineering standards for model selection, evaluation, testing, observability, and cost management.
- Operational ownership through on-call participation, incident response, and continuous feedback loops for retrieval and agent reliability.
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