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NetApp

Optimizes cloud infrastructure costs on AWS

AI Analyst

Manual & Functional QAUpdated on Nov 14
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree is required.
  • At least 7 years of experience in Business Analysis, Finance Analytics, or FP&A Operations is required.
  • Experience with AI-powered tools, chatbots, or conversational AI interfaces is required.
  • Understanding of Finance metrics and reporting, such as Bookings and Revenue, is required.
  • Working knowledge of SQL and Snowflake is required.
  • Understanding of AI and large language model fundamentals, including how models retrieve, process, and present information and awareness of hallucination, data staleness, and context window limitations, is required.
  • A Prompt Engineering Certificate or related experience is required.

Responsibilities

  • Gather and document business requirements from Finance users and stakeholders through interviews, workshops, observation, and feedback analysis.
  • Write clear, detailed user stories with well-defined acceptance criteria for IT implementation.
  • Ensure requirements reflect metric integrity standards and executive-readiness expectations.
  • Develop and maintain AI-specific testing frameworks, including test scenarios, expected outputs, edge cases, and pass/fail criteria tailored to conversational AI behavior.
  • Establish and document quality standards for AI-generated responses, including accuracy, completeness, formatting, tone, and contextual relevance.
  • Validate AI-generated responses against Snowflake source data using SQL queries to confirm metric accuracy and consistency.
  • Conduct user acceptance testing, regression testing, and release testing for new features, enhancements, prompt updates, data refreshes, and model changes before go-live.
  • Verify that Bookings and Revenue figures surfaced by AI match official Finance reporting.
  • Coordinate business sign-off workflows with Finance stakeholders before releases are promoted to production.
  • Design and execute validation test strategies targeting hallucination risks, including fabricated data, incorrect metric associations, misleading trends, and unsupported narratives.
  • Identify and catalog high-risk Finance use cases with elevated hallucination potential, such as multi-step calculations, year-over-year comparisons, segment-level breakdowns, and forecast-versus-actual analysis.
  • Monitor response quality through periodic spot checks and audits of AI outputs across query types and user scenarios.
  • Escalate suspected hallucinations and quality concerns to the Data Accuracy Specialist and team lead, and coordinate with IT and Engineering to implement fixes and guardrails.
  • Support the design and testing of executive-focused use cases to ensure AI responses meet the precision, tone, and contextual depth expected by C-suite and SVP users.
  • Test and validate executive prompt frameworks, including curated queries, guided flows, and personalized dashboards, for accurate and polished outputs.
  • Identify opportunities to improve usability and decision-support capabilities for the executive experience.
  • Develop and execute adoption strategies to drive Finance user engagement from initial awareness through active daily use.
  • Design and deliver onboarding experiences for new users, including guided walkthroughs, sandbox environments, and office hours.
  • Conduct live demonstrations, workshops, and drop-in training sessions tailored to analysts, managers, and directors.
  • Draft and distribute release notes, feature announcements, tips and tricks, known-issue updates, and adoption progress reports to Finance stakeholders.
  • Collect and synthesize user feedback through surveys, interviews, and usage analytics to improve the experience.

Desired Qualifications

  • Familiarity with Abacus or similar platforms.
  • Hands-on experience designing, testing, and refining prompts to improve AI response quality and accuracy.
  • Experience creating training materials, user guides, or knowledge base content.
  • Experience with AI testing frameworks or quality assurance for data-driven applications.
  • Familiarity with AI governance or responsible AI principles.

About the Company

NetApp

Optimizes cloud infrastructure costs on AWS

Spot.io, part of NetApp, helps businesses manage cloud costs and infrastructure on AWS. It uses software that analyzes cloud usage and automates management to lower compute expenses, especially through AWS EC2 spot instances, which offer spare capacity at reduced prices. The product provides deep visibility into cloud spending, an AWS cost optimization calculator for estimating potential savings, and a free action plan tailored to each customer. Revenue comes from selling software licenses and consulting services. Target customers include enterprises using containers and orchestration tools like Kubernetes, EKS, ECS, KOPS, Docker Swarm, and OpenShift. The company aims to reduce cloud compute costs for customers while simplifying cloud operations and improving efficiency.

Company size
51-200
Company stage
Acquired
Total funding
$53.2M
Headquarters
Tel Aviv-Yafo, Israel
Founded
2015

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