ML Engineer I

AI Engineer, AI-Enabled PMO Build agentic AI products that automate and improve enterprise PMO business processes FUNCTION Technology / IT PMO EMPLOYMENT Full-time EXPERIENCE 5+ years total; 2-3+ years AI Position Summary The AI Engineer will design, build, test, deploy, and continuously improve AI-enabled software products and intelligent agents that transform PMO processes. Working as part of a cross-functional product team, this role will convert PMO workflows, data, controls, and user needs into secure, reusable agent capabilities across demand and intake, project delivery, communications, reporting, portfolio management, business-case development, and related PMO services. The role partners closely with the AI Scrum Master, product and process owners, PMO leaders, engineers, data and platform teams, security, and business stakeholders. Success requires hands-on engineering depth, critical thinking, comfort with ambiguity, and the ability to move from problem definition through production-quality delivery. Key Responsibilities • Design and develop agentic AI solutions that automate PMO workflows, decisions, content generation, routing, approvals, estimation, status reporting, risk and dependency management, and portfolio insights. • Translate PMO use cases, process maps, personas, controls, source data, and desired outcomes into technical designs, user stories, acceptance criteria, prototypes, and production-ready software. • Build reusable agents, skills, tools, prompts, orchestration patterns, APIs, data connectors, and human-in-the-loop controls that can be shared across PMO products. • Develop primarily with Python and relevant AI, web, API, database, and cloud technologies; contribute to modern user experiences where required. • Integrate AI solutions with enterprise platforms and repositories such as JIRA, Confluence, SharePoint, collaboration tools, workflow platforms, and approved data sources. • Implement retrieval, grounding, memory/persistence, evaluation, observability, access control, auditability, privacy, and security patterns appropriate for enterprise PMO data. • Create test strategies and automated tests for functional accuracy, model/agent quality, reliability, performance, safety, regression, and user acceptance. • Participate in Agile ceremonies, estimate work, maintain technical backlog items, demonstrate working increments, and support disciplined release planning. • Partner with the AI Scrum Master to identify blockers, dependencies, capacity constraints, technical risks, and opportunities to improve delivery flow. • Produce concise technical documentation, architecture decisions, deployment notes, support procedures, and knowledge-transfer materials. • Support pilots, beta testing, user feedback, production release, operational handoff, and continuous improvement using measurable outcomes. • Contribute original solution ideas rather than waiting for detailed instructions; use AI as a design and engineering accelerator while applying sound judgment. Required Qualifications Area Requirement Education Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Science, Artificial Intelligence, or a closely related discipline. Experience Minimum 5 years of professional software development experience, including at least 2-3 years building, integrating, or operating software with AI or machine-learning capabilities. PMO environment Demonstrated experience working within or directly supporting a PMO, enterprise transformation office, project portfolio team, or comparable project delivery organization. AI delivery history Evidence of hands-on contribution to an AI-enabled software development team across requirements, design, coding, testing, deployment, and support. Candidates should be able to describe products delivered, their role, technical decisions, and measurable outcomes. Technical skills Strong Python skills; practical experience with APIs, databases, source control, CI/CD, cloud services, software testing, and secure enterprise application development. Agentic AI Experience with generative AI, LLM-based applications, prompt and context design, retrieval/grounding, tool calling, workflow orchestration, evaluation, guardrails, and human approval patterns. Certification At least one current, recognized AI or cloud-AI certification, such as Microsoft Certified: Azure AI Engineer Associate, AWS Certified Machine Learning Engineer, Google Cloud Professional Machine Learning Engineer, or an equivalent industry credential. Ways of working Experience in Agile product delivery using backlogs, user stories, acceptance criteria, iterative demonstrations, and release planning. Communication Ability to explain technical options, constraints, risks, and results to engineers, PMO practitioners, and senior stakeholders. Preferred Qualifications • Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field. • Experience developing multi-agent systems or enterprise workflow agents and integrating them with JIRA, Confluence, SharePoint, Microsoft 365, or similar platforms. • Experience with React or another modern front-end framework, relational/vector databases, cloud-native deployment, DevOps/MLOps/LLMOps, and telemetry. • Knowledge of responsible AI, threat modeling, data protection, identity and access management, confidentiality controls, and model/agent risk management. • Experience creating reusable engineering patterns across several products or Scrum teams in a shared portfolio. Success Measures • Working agent capabilities released against agreed acceptance criteria and business outcomes. • Reduced manual PMO effort, handoffs, rework, cycle time, or data inconsistency in targeted processes. • Reliable, secure, auditable solutions with appropriate human oversight and production support readiness. • Reusable technical components and documented patterns adopted across multiple PMO agent products. • Transparent delivery status, risks, dependencies, qua