Software Engineer III
Hybrid: Onsite at least 2 times per week at any of our locations - Quincy, MA, Carlisle, PA, Salisbury, NC, Chicago, IL, Greenville, SC, Scarborough, ME, Washington DC, Hyattsville, MD Overview As a Financial Systems Distributed Solutions Delivery Software Engineer, you will play a key role in delivering AI-infused, distributed financial solutions within a large retail grocery organization. This role focuses on supporting, integrating, and optimizing enterprise financial platforms that power high-volume processes such as Accounts Payable (AP), procurement, and related finance functions. You will work across a complex ecosystem of enterprise tools and cloud platforms to ensure secure, reliable data flow, system resilience, and operational performance. Emphasis is placed on solution design, logical problem-solving, and intelligent automation enablementwithout requiring hands-on application coding. Partnering closely with Finance, IT, and cross-functional teams, you will help deliver scalable solutions that incorporate AI-driven insights, automation, and analytics as business priorities evolve. Key Responsibilities Financial Systems Integration and Support Design, review, and support integrations across distributed financial systems (e.g., Coupa for procurement/spend, SAP for ERP/finance, and related enterprise platforms), ensuring accurate, compliant, and resilient data exchange in a high-transaction retail environment. AI-Infused Solution Delivery and Innovation Identify, evaluate, and support AI-enabled capabilitiessuch as intelligent automation, anomaly detection, predictive insights, and workflow optimizationto enhance financial operations, reduce manual effort, and improve decision-making across AP and procurement processes. Cross-Functional Collaboration and Process Improvement Partner with Business Analysts, Business Relationship Managers (BRMs), Finance, Procurement, and Operations teams to assess process inefficiencies and translate business needs into fundable IT initiatives, including AI-driven enhancements, for Finance leadership review. Cloud Architecture and Adaptability Contribute to solution design within hybrid and multi-cloud environments, with the ability to quickly learn and apply emerging cloud services, AI platforms, and integration patterns as business and technology landscapes evolve. Risk Management and Disaster Recovery Support risk assessments, regulatory and compliance requirements (e.g., SOX, data privacy), and disaster recovery planning to ensure business continuity, system resilience, and secure operation of financial platforms. System Monitoring and Observability Leverage monitoring and observability tools (e.g., Datadog, Reveille, or equivalent platforms) to track system health, performance trends, and issue resolution across distributed and AI-enabled solutions. Performance Analytics and Reporting Enable collection of operational and KPI data into Azure Data Lake and support Power BI dashboards that provide business visibility into system health, process efficiency, AI effectiveness, and overall IT solution performance. Continuous Improvement Proactively recommend enhancements to financial systems, integrations, and workflowsbalancing stability with innovationto align IT delivery with evolving retail finance objectives. Required Qualifications & Skills Education Bachelor's degree in Information Systems, Computer Science, Business Administration, Finance, or a related field (or equivalent professional experience). Experience 10 years of experience in IT roles supporting financial systems, integrations, solution delivery, or architecture within large-scale environments (retail, grocery, or other high-transaction industries preferred). Proven experience integrating and supporting distributed enterprise financial systems, including Coupa and/or SAP, and associated upstream/downstream platforms. Hands-on exposure to cloud-based solutions (hybrid/multi-cloud), system monitoring/observability tools (e.g., Datadog, Reveille, or equivalents), and analytics platforms such as Azure Data Lake and Power BI. Experience supporting or enabling AI-driven capabilities (e.g., automation, analytics, predictive insights) within enterprise or finance system contexts is strongly preferred. Demonstrated background in risk management, disaster recovery, and compliance for financial IT systems. Technical / Business Skills Strong understanding of distributed financial systems and AP-centric processes in retail or similar environments. Ability to assess, design, and support secure, scalable integration patterns, including governance controls (encryption, access management, SOX compliance). Logical, analytical troubleshooting skills for complex distributed environments, without requiring hands-on coding. Capacity to quickly learn and adapt to new tools, platforms, and AI technologies as business needs change. Soft Skills Excellent communication and collaboration skills for working with Finance, IT, and cross-functional stakeholders. Proactive, adaptable mindset with comfort operating in a fast-paced retail environment. Strong problem-solving, prioritization, and stakeholder management capabilities. Which financial systems are in active scope right nowCoupa, SAP, or other platformsand which ones will this role support most heavily? This role will focus on multiple finance systems, including Coupa and SAP, among others. The ideal candidate will be comfortable owning and managing multiple financial tools and processes. Can you describe the current integration landscape? What tools, middleware, APIs, or integration patterns are being used today? Our integration setup combines reliable, established patterns that support a segmented, data-sensitive environment (with appropriate network/firewall controls): File transfers using MQ/FTE or SFTP RESTful integrations (direct client/secret calls or via MuleSoft custom RESTful APIs) Database connections to MS/SQL and IBM DB2 using standard ODBC This foundation works well for our needs today, while the broader industry trends toward more reusable API-led approaches, event-driven flows, and intelligent middleware offer natural paths for future enhancement. What AI-driven or automation capabilities are already in place, and what new AI/ML initiatives do you expect this role to support? Our AI/ML initiatives are in the early stages, with proof-of-concept projects using Microsoft Azure (Computer Vision, OCR) to improve document processing. As an Engineer, you'll help define next steps, identify opportunities for intelligent automation, and ensure AI solutions deliver real business value responsibly, aligning initiatives with emerging priorities and governance standards. What monitoring and observability tools are currently implemented (e.g., Datadog, Reveille), and how mature is the monitoring environment? Reveille serves as our core Monitoring & Observability Platform (MOP) for the Content Management suite, with many years of reliable metric tracking and ongoing enhancements (e.g., expanding synthetic monitoring and data collection). Datadog was added more recently and performs well. The environment is mature in key areas, with active collaboration to broaden coverage and reduce business risk when systems operate outside expected ranges. There's opportunity to contribute to cross-team efforts for more consistent visibility. Is this role more focused on solution design and integration oversight, or is there any expectation of hands-on configuration or low-code work? The business has shared ongoing needs around improving accuracy, efficiency, and scalability in AP/procurement/financial operations. Much of the current process still relies on manual review and handling of physical documents (invoices, receiving docs, supporting forms), creating dependencies on external partners and affecting cashflow timing. This role would involve working with stakeholders to explore ways to ease those manual elementspotentially building on our Azure AI/OCR explorations or considering workflow adjustments. The emphasis is on collaborative evaluation and recommendations that gradually reduce paper dependency, enhance processing accuracy, and support better scalabilitypaced according to business priorities How is your cloud environment structured today - Hybrid or multi-cloud? Hybrid
