Senior AI Engineer (GRC)

TL;DR

Senior AI Engineer (GRC): Designing and delivering production AI systems for a continuous controls monitoring platform with an accent on data pipelines, agent orchestration, and RAG. Focus on building reusable AI primitives, optimizing model behavior in regulated domains, and ensuring enterprise-grade reliability.

Location: Remote (Must be a US Citizen)

Company

hirify.global is a continuous controls monitoring (CCM) platform that helps organizations automate and scale their security, risk, and compliance programs.

What you will do

• Design, build, and operate production AI systems with full ownership of reliability, performance, and cost.
• Develop data pipelines to ingest, clean, transform, and version data used by AI systems.
• Implement RAG pipelines, vector/graph search systems, and hybrid retrieval strategies for compliance data.
• Architect AI agent systems and orchestration layers for multi-step reasoning and tool use in GRC workflows.
• Build and maintain MCP servers to expose platform capabilities to AI systems.
• Create reusable AI primitives and frameworks to accelerate feature development across the organization.

Requirements

• Must be a US Citizen.
• 8+ years of software engineering experience, with at least 4 years focused on production AI/ML systems.
• Proven track record of shipping customer-facing AI features across the full production lifecycle.
• Strong expertise in RAG, vector/graph databases, embedding models, and hybrid retrieval.
• Experience designing AI agent systems and orchestration frameworks for production.
• Deep understanding of model fine-tuning and evaluation for domain-specific applications.

Nice to have

• Experience in regulated industries or GRC frameworks such as FedRAMP, NIST, or CMMC.
• Familiarity with Azure cloud-native AI infrastructure and model deployment.
• Experience with data lake solutions like Snowflake, Databricks, or AWS Redshift.
• Knowledge of inference cost optimization and caching strategies at scale.

Culture & Benefits

• Fully remote work environment.
• Opportunity to be part of a team transitioning from startup execution to a disciplined enterprise engineering organization.
• High level of ownership over the end-to-end design and delivery of AI systems.