AI Engineer

🕒 6 days ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Bridgeway Benefit Technologies

WebsiteLinkedInAll Job Openings

201 - 500 employees

☁️ SaaS

👥 HR Tech

SaaS • HR Tech

Bridgeway Benefit Technologies is a company that focuses on enhancing benefits administration solutions. It provides software and technology services to improve and streamline the management of employee benefits for businesses and organizations. The company aims to make benefits administration more efficient and user-friendly through its suite of technological tools.

📋 Description

• Contribute to the technical direction for AI-enabled systems in partnership with senior engineers and the architecture team. • Participate in design reviews for AI-adjacent features and incorporate feedback from senior engineers and architects. • Build production-quality Python services, pipelines, and integrations applying LLMs and retrieval to internal and product problems. • Integrate LLM APIs into existing systems using established guidance on model selection, cost profile, and failure handling. • Ensure AI capabilities honor schema-per-tenant and PHI-boundary patterns within the multi-tenant model. • Partner with the data and analytics team on retrieval- and LLM-backed features for the lakehouse and analytics layer, including embedding, chunking, retrieval evaluation, semantic search, summarization, anomaly narration, and contextual guidance. • Contribute to prompt libraries, evaluation frameworks, reference implementations, and reusable components; help refine standards for model selection, evaluation, testing, observability, and cost management. • Evaluate emerging AI tools and provide input on build-versus-buy decisions. • Build AI implementations compliant with HIPAA, SOC 2, and NIST, including PHI handling, data residency, audit logging, BAA coverage, prompt-injection defenses, LLM DLP, model access governance, and secrets handling. • Maintain documentation of AI systems, data flows, and risk assessments for audit and compliance review. • Collaborate with engineering, product, customer success, security, data, and operations to identify automation opportunities, translate them into technical plans, and contribute to the customer-facing AI roadmap. • Participate in operational quality and on-call rotation, including incident response, post-incident learning, observability, and feedback loops to improve retrieval quality, prompt behavior, and agent reliability. • Track production AI cost, quality, and adoption metrics and report outcomes to the manager, architecture team, and team leads. • Apply enterprise AI-integration best practices and share knowledge with peers.

🎯 Requirements

• 3–5 years of software engineering experience, with at least one year working on AI- or ML-backed systems, including contributions to at least one LLM-backed system in production. • Working knowledge of programmatic LLM orchestration, evaluation frameworks, and agent and tool-using systems, including exposure to securely connecting enterprise APIs to agentic systems. • Strong Python skills for production services, data pipelines, and integration work. • Experience building retrieval-augmented systems including familiarity with enterprise data architectures such as Databricks and Azure/AWS. • Strong written and verbal communication. • Familiarity with CI/CD, infrastructure-as-code, and MLOps practices for AI/ML systems. • Experience using generative AI tools such as Claude and Copilot to improve productivity and deliver high-quality outcomes. • Production experience in a regulated industry, with practical familiarity with HIPAA, SOC 2, or NIST, and with multi-tenant SaaS data isolation and identity/access patterns for B2B platforms (preferred). • Bachelor's or master's degree in Computer Science, Engineering, Data Science, or related field.

🏖️ Benefits

• Remote position • Equal Opportunity Employer