> Markdown version of [/jobs/ext/3997170-product-owner-post-trade-lifecycle-transformation](https://www.wearedevelopers.com/jobs/ext/3997170-product-owner-post-trade-lifecycle-transformation). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Product Owner - Post-Trade Lifecycle Transformation - **Company:** Macquarie Global Services - **Location:** Houston, TX, United States (Remote available) - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, E2e Testing, Large Language Models, AI Coding Agents, Agentic-AI, Event Driven Architecture, Data Pipelines - **Published:** October 28, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/88719690/1 ## About the Role * Exceptional product thinking in engineering-led environments - you shape what gets built and why * Experience building workflow systems, operational platforms, or trade lifecycle technology from the ground up * First-principles mindset - you don't optimise broken processes, you replace them * Comfort with ambiguity and speed - this is greenfield, fast-moving, and high-stakes * Proven ability to lead cross-functional teams (engineering, operations, data) and ship product that works * Experience or strong conviction in building with AI agents - you see them as force multipliers, not novelties Highly Desirable * Experience in post-trade operations, capital markets, or market infrastructure. * The initial focus will be on Physical Commodities from logistics to post-trade - Commodities experience would be welcome but not necessary * Familiarity with event-driven architectures, canonical data models, or trade lifecycle systems * Hands-on experience with AI coding agents, LLM-powered workflows, or agentic systems ## Description Today, millions of post-trade events are processed annually, underpinned by a staggering volume of manual adjustments across validations, settlements, and reconciliations. That's not a problem to manage. It's a problem to eliminate. We are seeking a Product Owner to join the team designing the Trade Lifecycle Operational Flow - the core engine that replaces manual, batch-driven post-trade processing with structured lifecycle events, a canonical data model, and straight-through processing. You'll be designing and delivering the system that makes zero manual adjustments a reality - leading hybrid teams of engineers and AI agents to build at a speed and quality the industry hasn't seen. If you're looking for a role where you maintain a backlog and attend standups, this isn't it. If you want to fundamentally rethink how post-trade works - keep reading. We are a global financial services group operating in 30 markets with 57 years of unbroken profitability. At Macquarie, you're empowered to shape a career that is fulfilling and creates value. You will bring your insights and expertise to the task at hand and feel supported as you make your own kind of impact for a better future. What role will you play? Press space or enter keys to toggle section visibility You'll own: Trade Lifecycle Operational Flow * Design structured lifecycle events that make downstream controls deterministic - not reactive * Define the canonical operational schema that standardises how trades flow through the lifecycle * Drive the engineering backlog from MVP through to production at scale End-to-End Integration * Work with Trade Capture teams to ensure upstream data quality eliminates downstream manual adjustments at source * Partner with Trade Lifecycle and Digital Channels squads to deliver cohesive end-to-end outcomes AI & Automation * Embed AI into the lifecycle - automated exception resolution, intelligent routing, predictive controls * Challenge every manual touchpoint: if it can be a rule, make it a rule; if it can be learned, train a model; if it shouldn't exist, kill it * Design systems where AI agents operate as first-class participants in the post-trade lifecycle - not bolted on, but built in Building with People and Agents * Lead hybrid teams where engineers and AI agents collaborate to design, build, test, and ship * Define how AI agents are deployed within your squads - as coding partners, testing agents, data pipeline builders, and operational executors * You're not managing a team that uses AI. You're building a team where AI is a teammate. Platform Delivery * Build internal-first with commercial potential - solutions designed to scale beyond a single business * Think in platforms, not projects