Technical Delivery Engineer

About Oversight Oversight is the leader in Finance Risk Intelligence, delivering AI-powered operational intelligence that helps Global 1000 finance teams identify, prioritize, and address financial risk with greater visibility, confidence, and control. Headquartered in Atlanta, GA, Oversight is purpose-built for enterprise finance and integrates across ERP, AP, T&E, procurement, P-cards, vendor statements, and payment systems to continuously analyze financial activity and transform fragmented data into actionable intelligence. By combining advanced AI, behavioral intelligence, and decades of finance risk expertise, Oversight helps organizations strengthen controls, automate low-risk resolution, and move from reactive reviews to continuous assurance in an increasingly complex financial environment. Recognized by Everest Group as a pioneer and leader in the emerging Finance Risk Intelligence (FRI) category, Oversight is helping define the future of AI-powered financial risk management. Position Overview: Job Purpose Oversight is seeking an experienced Technical Delivery Engineer to join the Onboarding organization. This engineer will support customer implementations, troubleshoot complex production issues, analyze cloud data pipelines, and help operationalize new platform capabilities. The ideal candidate thrives in fast-paced environments, works independently, embraces AI-assisted engineering, and can balance multiple customer implementations while delivering high-quality solutions. Responsibilities Support multiple concurrent customer implementation and production support engagements. Investigate complex customer issues across AWS, Databricks, PostgreSQL, SQL, and application services. Analyze, debug, and optimize SQL queries and data processing workflows. Collaborate with Forward Deployed Engineers to operationalize customer-specific solutions and transition them into standard product capabilities. Configure, validate, and troubleshoot cloud-based data pipelines and integrations. Use AI tools (ChatGPT, Cursor, Copilot, Claude, Gemini, etc.) to accelerate troubleshooting, documentation, scripting, and automation. Communicate technical findings clearly to internal teams and customer stakeholders. Continuously improve implementation processes, documentation, tooling, and operational efficiency. Balance priorities across multiple customers while maintaining high quality and responsiveness. Qualifications 3+ years in software implementation, technical delivery, support engineering, data engineering, or similar customer-facing technical role. Advanced SQL skills with the ability to debug and analyze complex queries. Experience with AWS services (including but not limited to S3, CloudWatch, Batch, Event Bridge) and Databricks. Experience with PostgreSQL. Experience with YAML development. Strong analytical troubleshooting and root-cause analysis skills. Experience working in high-volume, multi-project environments. Excellent written and verbal communication skills in a distributed/remote team. Demonstrated ability to make sound technical decisions with minimal supervision. Experience using AI as part of daily engineering workflows. Preferred Qualifications Financial services, banking, or enterprise financial data experience. Python scripting. Bitbucket/Git branching and Pull Request workflows. Experience in integrating customer solutions into productized implementations. Experience building AI agents or reusable AI workflows. API troubleshooting (REST/JSON). Experience using tools to track and measure the software implementation project metrics including quality and speed of the software implementation. Experience continuously improving the quality and speed of the software implementation process. Ability to debug and diagnose anomalies, issues and/or system gaps with curiosity, initiative and urgency. Experience facilitating meetings and gathering requirements. Excellent communication skills with the ability to translate technical concepts into clear, actionable guidance for both functional and technical customer stakeholders. Candidate Characteristics Self-starter who takes initiative rather than waiting for direction. Critical thinker capable of investigating unfamiliar technical problems. Comfortable switching between multiple tools and cloud platforms. Able to prioritize competing customer needs under pressure. Collaborative team player who shares knowledge and improves team processes. Growth mindset with enthusiasm for adopting emerging AI technologies.