Responsibilities
- Design and build the Finance-specific AI integration layer that connects AI systems to enterprise finance platforms, operational data, and institutional knowledge sources.
- Integrate AI systems with platforms such as NetSuite, Adaptive Planning, FloQast, AWS, and internal data warehouses.
- Build retrieval and knowledge systems over financial documentation, board materials, KPI definitions, investor communications, and forecasting models.
- Develop reusable AI workflow and orchestration patterns for Finance use cases.
- Enable conversational and natural-language interaction with operational and financial data.
- Partner with central Engineering and AI platform teams to adopt and extend shared AI infrastructure patterns.
- Design systems that allow Finance teams to progressively own configuration, evaluation, and operational management of AI workflows over time.
- Build AI-enabled quality assurance and validation systems that improve confidence, consistency, and operational rigor across Finance workflows.
- Implement metric reconciliation across reporting materials and presentations.
- Validate narrative and KPI consistency.
- Verify financial calculations.
- Ensure reporting integrity and formatting validation.
- Develop AI-assisted review workflows with human-in-the-loop oversight.
- Establish evaluation and auditability patterns supporting SOX-aligned processes where applicable.
- Develop evaluation frameworks and review processes to ensure AI systems are reliable, measurable, and operationally trustworthy.
- Develop AI systems that continuously analyze operational and financial processes to surface insights, anomalies, optimization opportunities, and business risks.
- Monitor cost and spend.
- Conduct vendor and procurement analysis.
- Perform contract and compliance monitoring.
- Analyze pricing and operational trends.
- Optimize cloud and AI platform costs.
- Implement automated summarization, alerting, and root-cause analysis.
- Build AI-powered intelligence capabilities to help Finance leadership monitor external market activity and prepare executive-level materials efficiently.
- Monitor competitor activity, earnings calls, filings, and analyst commentary.
- Support benchmarking and market intelligence workflows.
- Assist with earnings preparation, executive Q&A, and board preparation workflows.
- Cross-reference and validate data across financial narratives, trend reporting, and investor-facing materials.
- Develop AI-enabled workflows that accelerate operational execution and reduce manual effort across recurring Finance processes.
- Support monthly and quarterly reporting commentary.
- Generate flash reports and KPI summaries.
- Conduct forecast and enrollment analysis.
- Validate revenue and operational models.
- Support drafting of executive memos and board materials.
- Partner closely with Finance SMEs to ensure workflows remain operationally accurate, transparent, and trusted.
- Build evaluation frameworks, regression testing, and quality scorecards.
- Establish operational review and feedback loops.
- Train Finance SMEs on AI evaluation and workflow management.
- Promote transparency around AI capabilities, limitations, and reliability.
- Help Finance teams grow long-term AI fluency and operational ownership.
Requirements
- 5+ years of experience building and deploying software, data, automation, or AI-powered applications.
- 2+ years of recent hands-on experience building LLM-based or AI-enabled systems in production environments.
- Strong experience designing AI workflows including retrieval systems, orchestration patterns, tool usage, evaluation frameworks, and multi-step reasoning systems.
- Strong proficiency in Python and experience building production-quality backend services, APIs, integrations, and automation workflows.
- Experience integrating enterprise systems and operational data into AI-enabled workflows.
- Experience working with enterprise business systems such as ERP, planning, financial, or operational platforms.
- Experience designing retrieval or contextual knowledge systems across large document and metric corpora.
- Familiarity with structured and unstructured enterprise data environments.
- Understanding of operational monitoring, evaluation, and observability concepts for AI systems.
- Excellent communication and stakeholder management skills.
- Proven ability to partner directly with non-technical teams and translate business workflows into scalable technical solutions.
- Experience enabling business users through training, documentation, and operational coaching.
- Comfortable operating within highly cross-functional and rapidly evolving environments.
- Thrives in ambiguity and 0→1 environments.
- Strong ownership mentality with the ability to independently drive initiatives forward.
- Comfortable balancing embedded business partnership with centralized engineering alignment.
- Demonstrates strong prioritization and judgment across competing initiatives.
- Awareness of governance, security, and compliance considerations related to enterprise AI adoption.
- Familiarity working within regulated or compliance-sensitive environments involving financial, operational, or healthcare-related data.
- Comfortable incorporating human review, evaluation, and auditability into AI workflows.
Nice to Have
- Experience applying AI to Finance, Accounting, FP&A, Procurement, Revenue Operations, or operational business workflows.
- Experience working with platforms such as NetSuite, Adaptive Planning, FloQast, Workday, or enterprise data warehouse environments.
- Experience with AI orchestration frameworks such as LangChain, LangSmith, or similar tooling.
- Experience with AWS services, including Bedrock and modern cloud-native architectures.
- Experience extracting structured insights from unstructured enterprise documents using AI techniques.
- Prior experience operating as an embedded, Forward Deployed, Solutions, or customer-facing engineer.
- Strong perspective on responsible enterprise AI adoption and organizational AI enablement.
Benefits
- Competitive salary with generous annual cash bonus
- Equity grants
- Employee stock purchasing plan (ESPP)
- Remote first work from home culture
- Flexible Time Off to help you rest, recharge, and connect with loved ones
- Generous parental leave
- Health, dental, and vision insurance (and above market employer contributions)
- 401k retirement savings plan
- Lifestyle Spending Account (LSA)
- Mental Health Support Solutions
- ...and more!
Additional Information
- This role requires balancing speed, innovation, governance, operational reliability, and stakeholder alignment in a rapidly evolving AI landscape.
- The systems built will operate within a highly regulated and compliance-sensitive environment that includes SOX, HIPAA, security, and data governance considerations.
- The role evolves from hands-on builder into strategic architect and AI transformation leader over time.
