# Staff Engineer, AI Platform & Architecture (R5449) **Company**: Shield AI **Work arrangement**: remote **Experience**: staff **Job type**: full-time **Salary**: USD 190,000-290,000 per-year-salary **Category**: Engineering **Industry**: Technology **Apply**: https://jobs.lever.co/shieldai/ac728f5a-f0cb-41f4-876a-9b368b350782?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_efe3b813-d57 ## Description Shield AI is seeking a Staff Engineer, AI Platform & Architecture to translate the enterprise AI engineering roadmap into scalable platform architecture, reusable technical patterns, and production-grade shared services. The successful candidate will provide deep technical leadership across AI enablement, responsible AI controls, observability, cost attribution, and reusable component strategy. ## Responsibilities ### AI Platform Architecture & Standards - Define and evolve enterprise AI architecture patterns for LLM integration, retrieval-augmented generation, agentic workflows, prompt orchestration, and workflow automation. - Create reference architectures, design reviews, decision records, and implementation guidance that enable consistent AI development across business units. - Serve as a technical authority for AI platform decisions, including model selection, integration approaches, data boundary enforcement, and lifecycle management. - Evaluate emerging AI technologies and recommend fit-for-purpose adoption paths aligned to security, operational, and enterprise architecture requirements. - Partner with product, platform, and business technology teams to identify common needs and convert them into reusable engineering patterns. ### Reusable Components & Shared Services - Design and build reusable AI components such as connectors, agents, skill templates, prompt libraries, data pipelines, integration adapters, and service APIs. - Lead technical design for shared platform services for AI observability, logging, usage metering, evaluation, and lifecycle management. - Establish quality, versioning, deprecation, documentation, and contribution standards for the shared AI component catalog. - Guide teams through adoption of shared components, balancing standardization with practical implementation needs. - Identify opportunities to eliminate duplicate AI engineering efforts through consolidation, abstractions, and platformization. ### Responsible AI Engineering & Governance - Architect engineering controls for access management, data classification enforcement, prompt safety, output validation, audit logging, and policy adherence. - Partner with Security, Legal, and compliance stakeholders to embed responsible AI requirements into development and deployment pipelines. - Design model and agent lifecycle governance patterns, including version tracking, evaluation, drift monitoring, rollback, and deprecation workflows. - Build technical dashboards and telemetry that expose adoption, risk, performance, and governance compliance across AI-enabled systems. - Represent engineering considerations in AI governance reviews and translate policy requirements into implementable technical standards. ### Productivity, Measurement & Technical Leadership - Develop AI-assisted workflow patterns that improve individual productivity, team collaboration, knowledge retrieval, meeting intelligence, document generation, and task automation. - Design measurement approaches that connect AI usage to time savings, quality improvement, error reduction, capacity creation, and business value. - Partner with Finance and platform teams to develop cost metering, showback/chargeback, and optimization mechanisms for AI services. - Mentor senior and mid-level engineers, raise engineering quality, and lead complex cross-functional technical initiatives from concept through production. - Contribute to communities of practice, internal enablement material, and technical evangelism for enterprise AI engineering standards. ## Requirements - Progressive experience in enterprise software engineering, AI platform engineering, data platform engineering, or digital workplace technology roles. - Deep hands-on understanding of generative AI, large language model integration, RAG architectures, agentic AI patterns, prompt orchestration, and production AI system design. - Experience designing shared platform services, reusable component libraries, APIs, integration frameworks, or developer enablement platforms used by multiple teams. - Strong architecture judgment across security, reliability, scalability, observability, maintainability, and operational cost tradeoffs. - Experience implementing or contributing to AI governance controls such as access management, data classification, audit logging, model lifecycle management, and compliance-aware development practices. - Ability to influence technical direction across matrixed teams through architecture reviews, written guidance, reference implementations, and hands-on collaboration. - Experience defining metrics, telemetry, or attribution mechanisms for adoption, productivity, cost, quality, or operational performance. - Strong written and verbal communication skills with the ability to explain complex AI engineering concepts to technical and non-technical audiences. ## Skills ### Required - generative AI - large language model integration - RAG architectures - agentic AI patterns - prompt orchestration - production AI system design - shared platform services - reusable component libraries - APIs - integration frameworks - developer enablement platforms - AI governance controls - access management - data classification - audit logging - model lifecycle management - compliance-aware development practices ### Nice to have - MLOps - AI observability - model evaluation frameworks - agent evaluation - production monitoring - enterprise AI tooling ecosystems - copilot platforms - workflow automation suites - vector databases - enterprise search/RAG platforms - Databricks - Snowflake - lakehouse architectures - usage metering - cost allocation - showback/chargeback - AI spend optimization capabilities --- Source: [Apply at jobs.lever.co](https://jobs.lever.co/shieldai/ac728f5a-f0cb-41f4-876a-9b368b350782?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)