Job Details

Product Owner – Observe-to-Agent (O2A) Platform

Location: Charlotte, NC

Work Model: Hybrid, 3 days onsite per week

Contract Duration: 6-month W2 contract with potential to extend or convert

Pay Rate: $57–$61/hr W2, weekly pay

Start Date: ASAP

Calculated Hire is supporting a leading financial services client in their search for a Product Owner to support the enterprise Observe-to-Agent (O2A) platform. This role will focus on building and scaling an advanced AI and automation capability that transforms observed business workflows into executable agentic workflows, automation code, and reusable process intelligence.

Job Description

The Product Owner will lead the vision, roadmap, and enterprise development of the Observe-to-Agent platform. This platform is designed to convert workflow observations, video-based process captures, clickstream data, and business process insights into actionable automation opportunities and agentic AI capabilities. This role sits at the center of business process understanding, multimodal AI, automation engineering, and enterprise digital transformation.

The ideal candidate will be able to understand complex business processes, define product strategy, partner with engineering and AI teams, and translate operational workflows into scalable automation and agentic platform capabilities.

The Product Owner will work closely with business sponsors, operations SMEs, data science teams, AI engineering, platform engineering, SKAN/SkanAI configurators, and application teams to define requirements, prioritize capabilities, and drive delivery across the Observe-to-Agent lifecycle.

Responsibilities

• Own the product vision, roadmap, and multi-release strategy for the Observe-to-Agent platform.
• Define and scale enterprise capabilities that support workflow observation, process intelligence, agentic automation, and automation code generation.
• Partner with business and technology stakeholders to understand current-state workflows, operational pain points, and automation opportunities.
• Translate observed business processes into clear product requirements, automation-ready features, and engineering-aligned deliverables.
• Support the end-to-end O2A lifecycle, including Observe, Analyze, Optimize, and Run.
• Partner with engineering, AI, data science, and platform teams to shape the transition from workflow capture to agent execution.
• Help define enterprise patterns for converting video-based process captures, clickstream data, and workflow observations into executable agentic workflows or automation code.
• Own requirements for capabilities such as multimodal ingestion, SOP generation, workflow translation, semantic graph construction, agent execution validation, and multi-agent orchestration.
• Partner with SKAN/SkanAI and internal technology teams to support process capture, telemetry ingestion, persona configuration, clickstream processing, and data collection across business domains.
• Develop frameworks for process mapping, process mining, behavioral clustering, and insight generation to identify high-value automation opportunities.
• Define requirements for platform services such as structured insight extraction, ontology generation, knowledge graph generation, clickstream mapping, and automated workflow generation.
• Collaborate with technical teams on integration points, application impacts, governance standards, and implementation dependencies.
• Shape quality, governance, and assurance requirements, including PII redaction, safe-use patterns, model assurance, hallucination controls, rollback mechanisms, analyst-in-the-loop checkpoints, and observability.
• Establish release, change-management, onboarding, training, and readiness routines for enterprise O2A adoption.
• Work with SMEs across operations, fraud, complaints, IT operations, contact centers, and other business areas to translate manual workflows into reusable automation patterns.
• Communicate product vision, roadmap decisions, risks, dependencies, and delivery progress to senior leaders and cross-functional stakeholders.

Required Skills

• 7+ years of digital product management, product ownership, AI platform, automation platform, business transformation, or related experience.
• Strong product ownership experience, including roadmap creation, prioritization, backlog management, requirements definition, and multi-release planning.
• Experience supporting AI-enabled, automation-focused, or digitally enabled transformation initiatives.
• Strong understanding of business processes with the ability to communicate with stakeholders, understand operational workflows, and identify automation opportunities.
• Hands-on or strong working knowledge of agentic AI, GenAI workflows, AI agents, LLM-enabled automation, or automation architecture.
• Ability to understand the design and architecture of agentic implementation and translate that into scalable product requirements.
• Experience partnering with engineering, application, data science, AI/ML, platform, or automation teams.
• Ability to understand tool integrations, application impacts, data flows, and technical dependencies well enough to drive conversations with engineers.
• Strong systems-thinking mindset with the ability to design scalable, compliant, enterprise-grade AI or automation capabilities.
• Proven ability to influence senior leaders, technical teams, and business stakeholders while shaping strategy and prioritization.
• Strong communication skills with the ability to translate complex technical and business concepts into clear, actionable direction.

Desired Skills

• Experience with SKAN.ai, SkanAI, process mining, task mining, process intelligence, workflow observation, or clickstream analytics tools.
• Experience with multimodal AI, video-to-code, video-based process capture, semantic understanding, workflow translation, or automated code generation.
• Experience with RPA, intelligent automation, UiPath, Automation Anywhere, Blue Prism, Power Automate, or similar automation platforms.
• Experience with AI/ML platform services, ontology generation, knowledge graphs, large action models, or structured insight extraction.
• Experience with governance, model assurance, PII redaction, safe-use patterns, quality controls, execution validation, or enterprise AI risk management.
• Experience with observability or monitoring tools such as Splunk, Arize, Phoenix, or similar platforms.
• Financial services, banking, operations, risk, fraud, complaints, IT operations, or contact center transformation experience.

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