Senior AI Value Stream Engineer

Core Responsibilities

• Manage day-to-day project activities and oversee comprehensive IT project operations as the primary single point of contact.
• Identify operational risks, establish issues tracking metrics, and recommend targeted technical risk mitigation strategies.
• Facilitate strategic alignment discussions and cross-functional meetings between agency stakeholders and external contractors.
• Monitor project timelines to ensure that performance matches defined scope, meets technical requirements, and delivers on time and within budget.
• Define critical deployment paths, core tasks, operational dates, technical testing, and stakeholder acceptance criteria.
• Enforce strict adherence to state Software Development Life Cycle (SDLC) design standards.
• Deliver innovative process solutions to maximize budget efficiency and reduce execution costs while maintaining high-performance levels.
• Document and deliver formal project management artifacts, lifecycle blueprints, and real-time status updates.
• Optimize AI workflows by identifying and removing operational bottlenecks related to data acquisition, model training, and ethical review cycles.
• Integrate Scaled Agile Framework (SAFe) environments with active Machine Learning pipelines to ensure experimentation phases transition smoothly into production delivery phases.
• Define, map, and track AI-specific key performance indicators (KPIs) including inference cost vs. value, model accuracy over time, and task automation return on investment (ROI).
• Act as an AI Governance Liaison alongside the Security Officer to embed compliance architectures, bias testing, and security guardrails into the Agile Release Train (ART).
• Cook up vendor and open-source model evaluation strategies to ensure technical tools match long-term value stream architectures.
• Coach scaling Agile engineering teams through complex technical transitions.

Required Qualifications & Skills

• A Bachelor's degree from an accredited college or university in an IT, business, or related scientific discipline.
• A minimum of 4 years of hands-on experience managing complex IT software development projects.
• At least 3 years of experience operating with a strong foundational knowledge of SAFe working methodologies.
• A minimum of 2 years of active experience in SAFe environments, with a proven ability to adapt Lean-Agile principles to data-heavy or algorithmic projects.
• At least 2 years of dedicated experience managing complex IT projects specifically involving Natural Language Processing (NLP), Predictive Analytics, or Generative AI.
• Proven experience serving in a leadership capacity for at least 2 successful projects containing an organizational change management component.
• Demonstrated history leading at least 2 successful projects involving change management frameworks that trained non-technical staff to adopt AI tools.
• Native or bilingual English language proficiency.

Preferred Qualifications & Skills

• Demonstrated experience overseeing the transition of AI/ML projects from Proof of Concept (PoC) to full-scale production.
• Experience managing variable cloud compute budgets, tracking GPU usage, and measuring API consumption costs.
• Comprehensive understanding of the "Data-to-Model-to-App" pipeline with an ability to bridge technical communications between data scientists and infrastructure teams.
• Specialized experience identifying and mitigating distinct AI risks, including Data Drift, Model Hallucinations, and Algorithmic Bias.
• Knowledge of foundational DataOps and MLOps operational principles.