AI Product Owner

Raas Infotek; Redmond; On-site; AUD 171,000 - 256,000; Full time

Job summary

Raas infotek corporation seeks a hands-on AI Product Owner to join its Forward Deployed Engineering squad, a small team that works directly with customers to turn high-value business problems into production AI solutions in weeks.

The ideal candidate is fluent in Generative AI, LLMs, and RAG; comfortable prototyping; and driven by business impact. You will be the voice of the customer inside the squad and the squad with customer leadership.

Qualifications

• Bachelor’s degree in CS/Engineering, Data Science, or related field.
• 7+ years in product management, ownership, or related roles.
• 2+ years delivering GenAI/LLM/agentic AI into production.
• Hands-on with prompt engineering, RAG, vector databases, agent frameworks, and API/tool integration.
• Ability to build working prototypes with low-code tools.

Responsibilities

• Embed with customer teams to understand workflows, pain points, and data.
• Frame problems into testable hypotheses and define what good looks like.
• Prototype hands-on using prompt engineering, low-code agent tools, and AI platforms.
• Own the squad backlog with lean user stories and acceptance criteria.
• Partner with the AI Architect on agent design, tool and API integrations, RAG strategy, and model selection.
• Define and own evaluation sets (golden datasets, test cases, rubrics).
• Make pragmatic trade-offs between quality, latency, cost, and risk and explain them to stakeholders.
• Drive solutions from pilot to production, including security, compliance, and operational readiness.
• Own adoption: onboarding, feedback loops, telemetry, and iteration after go-live.
• Measure and report business impact and build the case for scaling or stopping.
• Apply Responsible AI principles, guardrails, and monitoring for drift and misuse.
• Capture reusable patterns and playbooks to speed future engagements.
• Build trusted relationships with customer leaders and identify follow-on opportunities.

Skills

Prompt engineering

Backlog management

Stakeholder management

Low-code agent tools

Generative AI

Customer facing

Education

Bachelor's degree in Computer Science & Engineering, Data Science, or related field

Tools

Agent frameworks

Vector databases

API integration

Azure OpenAI

Power Platform

Job description

Visa: Only visa independent candidates. Only W2 candidates.

Experience: Minimum 10+ years of experience.

Job Summary

We are seeking a hands-on AI Product Owner to join our Forward Deployed Engineering (FDE) squad, a small, embedded team that works directly with customers to turn high-value business problems into production AI solutions in weeks, not quarters.

This is not a traditional product management role. You will sit alongside customer stakeholders and engineers, discover where AI can create measurable value, shape the solution in real time, and own the outcome from first prototype through production adoption.

The ideal candidate is technically fluent in Generative AI, Agentic AI, LLMs, and RAG; comfortable building and testing prototypes themselves; and driven by business impact rather than process.

You will act as the voice of the customer inside the squad and the voice of the squad with customer leadership.

Key Responsibilities

• Embed with customer teams to understand workflows, pain points, and data, and identify the highest-value AI and agentic use cases.
• Rapidly frame problems into testable hypotheses, and define what “good” looks like before anything is built.
• Prototype hands-on using prompt engineering, low-code agent tools, and AI platforms to validate ideas with users within days.
• Own the squad backlog in ADO, writing lean user stories and acceptance criteria tied to business outcomes, not just features.
• Partner with the AI Architect and Forward Deployed Engineers on agent design, tool and API integrations, RAG strategy, and model selection.
• Define and own evaluation sets (golden datasets, test cases, rubrics) and use eval‑driven development to decide when a solution is ready to ship.
• Make pragmatic trade‑offs between quality, latency, cost, and risk, and explain them clearly to customer stakeholders.
• Drive solutions from pilot to production, including security, compliance, and operational readiness.
• Own adoption: user onboarding, feedback loops, telemetry, and iteration after go‑live.
• Measure and report business impact (time saved, cost reduced, quality improved) and build the case for scaling or stopping.
• Apply Responsible AI principles, including guardrails, human‑in‑the‑loop design, hallucination handling, and monitoring for drift and misuse.
• Capture reusable patterns, components, and playbooks so each engagement makes the next one faster.
• Build trusted relationships with customer leaders and identify follow‑on opportunities.

Required Qualifications

• Bachelor’s degree in Computer Science & Engineering, Data Science, or a related field (or equivalent experience).
• 7+ years in product management, product ownership, technical program management, solutions engineering, or consulting.
• 2+ years hands‑on delivering GenAI, LLM, or agentic AI solutions into production (not only roadmaps or strategy).
• Practical experience with prompt engineering, RAG, vector databases, agent frameworks, and tool/API integration.
• Ability to build working prototypes yourself (low‑code agent builders, notebooks, scripting, or similar).
• Experience designing AI evaluations and quality metrics for LLM‑based systems.
• Understanding of AI architecture, APIs, data integration, LLMOps, and production readiness.
• Comfort working directly with customers in ambiguous, fast‑moving environments.
• Strong prioritization and the judgment to say no, or to stop work that is not delivering value.
• Excellent communication and storytelling, including executive‑level stakeholder management.
• Bias for action and ownership of outcomes.

Preferred Qualifications

• Prior experience in a forward deployed, solutions engineering, or customer‑embedded delivery model.
• Experience building Copilots, multi‑agent systems, or enterprise agentic workflows.
• Familiarity with Azure AI Foundry, Azure OpenAI, Copilot Studio, Power Platform, and the Microsoft Copilot ecosystem.
• Experience with AI governance, Responsible AI, and enterprise security and compliance reviews.
• Knowledge of telemetry, product analytics, A/B testing, and adoption measurement.
• Basic Python or similar coding skills.

Deepak Singh

Raas infotek corporation

262 Chapman road, Suite 105A, Newark, DE-19702

Phone: [phone] Ext: 140,

LinkedIn: linkedin.com/in/deepak-singh-86969b423