Hands-on AI engineering, solution architecture and compliance-by-design for enterprise Finance, operations and business systems
ROLE SCOPEResponsibilitiesThe role is accountable for hands-on delivery and architecture within its layer, with shared governance across BIS, Finance, Business Operations, IT and Security and active partnership with other enterprise functions.
AI solution architecture- Design end-to-end agentic solutions and determine when a use case should query a source system directly versus use the unified data model.
- Partner with stakeholders to identify high-value use cases, translate requirements into controlled AI workflows and select AI, conventional automation or no new technology.
- Create reusable architecture patterns for agents, tools, APIs, MCP servers, prompts, evaluations and human-review workflows.
- Produce solution designs, security flows, deployment patterns and technical standards.
AI engineering and system enablement- Build AI agents, orchestration services, enterprise applications and reusable platform components.
- Deliver workflows for close and reporting, procurement, forecasting, billing and compliance monitoring where AI adds measurable value.
- Establish secure, primarily read-only AI connections to approved business systems, beginning with NetSuite and extending to adjacent Finance and enterprise platforms as priorities evolve.
- Preserve source-system authentication, authorization, user-level entitlements, rate limits and audit trails.
- Implement citations, evidence links, deterministic checks, exception handling and safe action boundaries.
Prototype-to-enterprise delivery- Assess business-built or rapidly developed prototypes for value, architecture, security, maintainability and control readiness.
- Refactor or rebuild approved prototypes into tested, monitored and supportable enterprise applications.
- Establish development, test and production environments, release pipelines, incident response and rollback controls.
AI platform strategy- Evaluate AI models, agent frameworks, connectors and enterprise platforms on a regular cadence.
- Run structured proofs of concept and assess security, accuracy, integration, scalability, experience, cost and vendor viability.
- Maintain platform standards and recommend adoption, retention, replacement or retirement decisions.
Organizational enablement and adoption- Create clear documentation, reusable patterns and reference architectures; coach teams on effective agent design, prompts, evaluation practices and safe operating boundaries.
- Establish feedback loops with users and process owners; use adoption, task success, efficiency, trust and support signals to guide iteration.
Finance, SOX and compliance- Translate Finance, Security, Privacy, SOX and SSDLC requirements into technical architecture and application controls.
- Implement least privilege, segregation of duties, logging, retention, evaluation, change control and audit evidence.
- Require deterministic validation and reconciliation for financially material outputs.
- Support SOX walkthroughs, control testing, audits, risk assessments and remediation while escalating formal approval to control owners.
CANDIDATE PROFILEQualifications, success measures and boundariesRequired capabilities are calibrated for a Staff-level hands-on engineer with solution-architecture responsibilities.
Required qualifications- 8+ years in software, platform, integration, solution engineering or enterprise applications, including meaningful hands-on production ownership in complex environments.
- Strong Python and/or TypeScript skills; experience with APIs, MCP or comparable tool protocols, enterprise authentication and distributed-system design.
- Practical experience building production AI systems using agents, tool use, retrieval, structured outputs, evaluations and monitoring.
- Practical familiarity with leading LLM platforms and agent frameworks, such as OpenAI, Anthropic, Gemini, LangChain, Semantic Kernel or comparable technologies, including prompt and context engineering.
- Strong solution-architecture judgment across security, reliability, performance, cost, observability and supportability.
- Working knowledge of enterprise Finance processes such as general ledger, close, reporting, procure-to-pay, order-to-cash, forecasting and management reporting.
- Working knowledge of compliance-by-design, including access, segregation of duties, change management, interfaces, automated controls, completeness and accuracy, and audit evidence.
- Ability to communicate with engineers, Finance leaders, control owners, Security and executives.
Preferred qualifications- Experience with ERPs, data platforms, frontier AI platforms, agent frameworks or comparable enterprise technologies.
- Experience building internal enterprise applications.
- Hands-on experience implementing SOX controls or operating in a public-company or audit-regulated environment.
Success measures- Time from approved use case to controlled production and sustained adoption, with evidence of measurable business value.
- Reduction in manual effort and business-process cycle time; improvement in decision quality or service levels.
- Accuracy, groundedness, reconciliation success and production reliability of deployed agents.
- User adoption, task success, stakeholder trust and support burden for production workflows.
- Latency, operating cost and cost per successful task for deployed agents and applications.
- Reuse of approved architecture patterns and components across use cases.
- Number of viable prototypes transitioned into governed enterprise solutions.
- Security, SOX and audit findings; evidence completeness; incident rate and remediation time.
- Quality and timeliness of AI platform evaluations and roadmap recommendations.
