AI Platform Engineer

About us:Intuitive is an innovation-led engineering company delivering business outcomes for 100's of Enterprises globally. With the reputation of being a Tiger Team & a Trusted Partner of enterprise technology leaders, we help solve the most complex Digital Transformation challenges across following Intuitive Superpowers: Modernization & Migration • Application & Database Modernization • Platform Engineering (IaC/EaC, DevSecOps & SRE) • Cloud Native Engineering, Migration to Cloud, VMware Exit • FinOps Data & AI/ML • Data (Cloud Native / DataBricks / Snowflake) • Machine Learning, AI/GenAI Cybersecurity • Infrastructure Security • Application Security • Data Security • AI/Model Security SDx & Digital Workspace (M365, G-suite) • SDDC, SD-WAN, SDN, NetSec, Wireless/Mobility • Email, Collaboration, Directory Services, Shared Files Services Intuitive Services: • Professional and Advisory Services • Elastic Engineering Services • Managed Services • Talent Acquisition & Platform Resell Services About the job:Title: AI Platform EngineerStart Date: Immediate# of Positions: 1Position Type: Contract/ Full-time EmploymentLocation: Remote across USA (preferred Chicago, IL) About the RoleClient is seeking an AI Platform Engineer to bridge our current cloud and DevOps operations with our next-generation AI-powered development platform. This is an individual contributor role on the AI & Cloud Operations team — you'll own the platform underpinning our DevOps practice (AKS, CI/CD, IaC, and operational excellence) while equally driving AI development pipeline strategy, MCP server infrastructure, and the modernization of our delivery toolchain and developing AI Agents using within various AI platforms such as Claude, Gemini, Sierra and DevRev. This is a hands-on role with DevOps experience, cloud knowledge and previous AI Agent development and deployment. What You'll Own Key ResponsibilitiesProduction Readiness Assessment• Receive prototype applications and conduct structured assessments covering security posture, data model integrity, authentication and authorization flows, input validation, dependency hygiene, and test coverage quality• Identify and document failure patterns endemic to AI-generated code including hardcoded secrets, flat or unindexed schemas, missing error handling, and hallucinated or unpinned dependencies• Produce clear remediation plans with prioritized findings, working within the architectural standards set by the Full-Stack Systems Architect• Hands on experience building Agentic Agents in Gemini/Vertex, OpenAI, Claude or similar tools Code Remediation & Hardening• Refactor and harden AI-generated codebases to meet enterprise production standards across frontend frameworks, backend APIs, data modeling, and authentication systems• Replace or rewrite AI-generated test suites against human-reviewed acceptance criteria, ensuring coverage reflects real production behavior rather than checkbox validation• Use AI-augmented development tools (Cursor, Claude Code, GitHub Copilot) to accelerate remediation work while exercising independent judgment on when AI tooling is introducing new risk Security & Compliance• Identify and remediate common security vulnerabilities including injection flaws, broken authentication, insecure direct object references, and exposed secrets or credentials• Implement and validate secure authentication and authorization patterns in accordance with enterprise security policies• Ensure applications meet CI/CD pipeline requirements and version control standards prior to production deployment Pattern Recognition & Knowledge Management• Document recurring AI code failure patterns and contribute to a growing internal knowledge base• Feed pattern intelligence back upstream to improve prototype quality at the source, collaborating with developers and architects to reduce remediation burden over time• Stay current on AI-assisted development tooling, emerging failure modes, and production readiness best practices Collaboration & Communication• Partner with application teams, architects, and business stakeholders to align on readiness criteria and timelines• Communicate technical findings clearly to both engineering and non-technical audiences• Provide guidance and thought leadership on responsible use of AI development tools within the engineering organization QualificationsCore Engineering• Strong full-stack fundamentals across at least one major frontend framework (React, Vue, Angular), backend API development, relational data modeling, and authentication systems• Proficiency in Python, JavaScript/TypeScript, and at least one additional backend language• Solid understanding of RESTful API design, database schema design, and ORM patterns• Experience with version control discipline, branching strategies, and code review processes AI Code Failure Pattern Recognition• Strong ability to identify AI-generated code failure modes: hardcoded credentials, hallucinated libraries, flat schemas, checkbox