Senior AI Engineer

3 weeks, 5 days ago
Full-time
Lead
Software Development
RegScale

RegScale

RegScale offers an automated governance, risk, and compliance software platform that enables organizations to streamline their compliance programs through continuous controls monitoring and real-time evidence collection.

Utilities
11-50
Founded 2021
$22M raised

Description

  • Design, build, and operate production AI systems with ownership of reliability, performance, cost, observability, and model behavior.
  • Build and maintain data pipelines that ingest, clean, transform, and version AI-dependent data.
  • Design and implement retrieval augmented generation pipelines, vector and graph search systems, and hybrid retrieval strategies.
  • Fine tune, evaluate, and monitor models against real-world performance criteria.
  • Architect and build AI agent systems and orchestration layers for multi-step reasoning, tool use, and decision making.
  • Build and maintain MCP servers that expose platform capabilities to AI systems.
  • Design reusable AI primitives and frameworks that other teams can build on.
  • Integrate AI capabilities into CI/CD pipelines with testing, evaluation gates, and deployment strategies.
  • Partner with Platform Engineering, Core Engineering, and Compliance as Code teams to meet reliability and security standards.
  • Identify risks in AI behavior, data quality, and model performance and propose mitigations before incidents occur.

Requirements

  • 8+ years of software engineering experience, including at least 4 years building and operating AI or machine learning systems in production.
  • Proven track record of shipping AI features customers depend on across the full production lifecycle.
  • Strong data engineering fundamentals, including pipeline design, data modeling, transformation, quality validation, and performance monitoring at scale.
  • Hands-on experience with retrieval augmented generation, vector and graph databases, embedding models, and hybrid retrieval strategies.
  • Experience designing and building AI agent systems and orchestration frameworks, including multi-step reasoning, tool use, and failure handling.
  • Solid understanding of model fine tuning and evaluation for domain-specific applications.
  • Strong software engineering fundamentals applied to AI systems with production-grade rigor.
  • Strong written and verbal communication skills for technical and non-technical stakeholders.
  • Experience building AI systems in regulated industries or compliance-focused platforms (preferred).
  • Familiarity with secure MCP server development, GRC frameworks such as FedRAMP, NIST, or CMMC, Azure or comparable cloud AI infrastructure, and data lake tools such as Snowflake, Databricks, Synapse Analytics, or AWS Redshift (preferred).

Interested in this position?

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