Screening requirements (please read first):
- Non-negotiable: hands-on experience with process mining or task mining and ML/AI models used to analyze operational workflows (workflow discovery, variants, bottlenecks, cycle time, handoffs, deviations).
- Required: a 2β5 minute intro video link in your resume or via the platform (smartphone recording is fine). Applications without the video may not be reviewed.
Company overview:
Graphio.ai stops revenue loss before it happens by detecting broken handoffs between teams.
We analyze API-enabled metadata from your existing systems to automatically identify when Sales, Customer Success, Legal, Finance, Product, and Operations are misaligned - before deals stall, renewals fail, or contracts slip.
No workflow changes. Fast rollout in less than 2 days.
AI learns what successful execution looks like in your company and alerts you to dangerous deviations in real time.
Weβve built and scaled before: the team behind Graphio.ai previously built upSWOT, a B2B platform adopted by hundreds of financial institutions, which was later acquired by Uptiq. Weβre applying those lessons in execution, delivery, and scale to Graphio.ai.
Supported by senior leaders from Experian, Mastercard, Lattice, BambooHR, Altrata, SAP, JackHenry, FIS, Pfizer, Workday, Customertimes, and more (graphio.ai/investors).
Position Overview:
We are looking for a Senior Product Business Analyst (AI/ML) to help us build a polished, user-ready product experience around Graphio.aiβs core mission: stopping revenue loss before it happens by detecting broken handoffs between teams.
In this role, you will translate complex cross-functional execution problems into clear product requirements, data definitions, and measurable validation criteria. You will work closely with the Product Manager, Machine Learning and AI specialists, and Software Engineers to define what βsuccessful executionβ looks like for customers, turn that into reliable detection and alerting behavior, and continuously improve signal quality using API-enabled metadata from existing systems.
This role is rooted in B2B SaaS execution workflows, where multiple teams and systems must stay aligned for deals, renewals, and contracts to move smoothly. Your work will directly impact how accurately Graphio.ai detects misalignment early, how actionable the alerts are, and how fast customers see value after launch.
Key Responsibilities:
- Partner with the Machine Learning Engineer to define how the system automatically discovers and constructs the golden path (ideal workflow / best-performing execution pattern) from API-enabled metadata - including inputs, assumptions, and expected outputs.
- You will not manually build or validate customer workflows. Your role is to define requirements, data definitions, and evaluation criteria so the model generates the ideal workflow reliably and consistently.
- Translate customer process reality into clear modeling requirements: what a workflow step is, how handoffs are represented, how similar workflows are grouped, and how βsuccessful executionβ is determined at scale.
- Define API-enabled metadata requirements needed for automated modeling: event taxonomy, entities, identifiers, timestamps, ownership fields, system-of-record rules, and data quality constraints.
- Specify deviation definitions relative to the golden path (ideal workflow): missing step, wrong sequence, excessive delay, broken ownership transition, stalled handoff - and how deviations should be prioritized.
- Work with Engineering and Machine Learning to ensure modeling outputs are product-ready: stable, consistent across updates, and understandable enough for the end user to act on.
- Own the user-facing capability to review and edit the golden path (ideal workflow): allow customers to add/remove steps and adjust what βgood executionβ means, while preserving a reliable baseline generated by the system.
- Define and continuously improve weekly/monthly reporting: what insights are surfaced, how they are explained, and how reports/alerts are delivered to the accountable owner (a specific responsible person).
- Establish evaluation and monitoring for automated modeling and deviation detection: track misses vs false alarms, consistency of the generated ideal workflow, lead time gained, and actionability tied to revenue outcomes.
- Investigate accuracy issues: analyze why the system generated an incorrect ideal workflow or missed a deviation, propose improvements, and validate fixes through regression checks.
- Maintain a library of reference workflows and test scenarios that represent common cross-team handoff patterns and failure modes in workflow-driven B2B environments.
Preferred Qualifications:
- Experience building or supporting AI/ML-enabled B2B SaaS products, especially where models drive user-visible workflows and decisions.
- Hands-on experience working with event-based data and operational systems (for example: CRM, customer success platforms, ticketing systems, project management tools, finance/contract systems).
- Familiarity with workflow analytics / process mining concepts (workflow reconstruction, handoffs, cycle time, bottlenecks, variants).
- Experience defining data contracts: event taxonomy, entity identifiers, timestamp conventions, ownership fields, and data quality rules.
- Background in designing evaluation and monitoring for model-driven product behavior (false positives/negatives, consistency, drift, and business impact).
- Exposure to LLM-powered features (structured prompting, quality criteria, safety constraints, and human review loops), with a product mindset rather than research focus.
- Ability to create and manage reference scenarios and test libraries that represent real enterprise workflows and edge cases.
- Comfort collaborating across Product, Machine Learning, and Engineering teams in an agile environment, with strong written documentation skills.
- Experience working in workflow-heavy domains such as Revenue Operations, Customer Success Operations, Deal Desk, Legal Operations, Finance Operations, or Project Delivery.
- Prior work in early-stage or fast-scaling environments where you owned problems end-to-end and shipped iteratively.
What we offer:
- A role where you actually own a meaningful slice of the product (how the ideal workflow is defined, how deviations are detected and explained, how reports work).
- Close, practical collaboration with the Machine Learning Engineer and Software Engineers to ship improvements - not just write specs.
- Clear success criteria: fewer false alarms, fewer missed deviations, better weekly/monthly reports, faster time-to-value for customers.
- A fast feedback loop: youβll work with real customer workflows (metadata only), learn what breaks, fix it, and see results quickly.
- Exposure to real cross-team execution in companies: Sales, Customer Success, Legal, Finance, Product, Operations - and how handoffs impact revenue.
- Remote-friendly team with a simple setup and low overhead.
- Competitive compensation and room to grow as the product and team scale.
Company Operating Requirements:
At Graphio.ai we run a high-ownership, mission-driven team with clear operating rules. Please read these carefully before applying:
- LinkedIn profile is required (company policy). Employees are required to keep a current LinkedIn profile that shows their Graphio.ai position and is linked to the official Graphio.ai company page (company logo visible on the profile). Profile standards are provided during onboarding.
- Synchronized team vacations. The team takes coordinated time off four times per year to keep planning aligned and reduce context switching. Dates are announced in advance.
- Startup constraints. Vacation timing may be restricted during critical company periods. We plan time off as a team and communicate constraints early.
- Relocation readiness. Team members may reside in Ukraine, but must be prepared to relocate with their families to Europe or the United States if the company requests it and it becomes legally possible. Any relocation would be discussed in advance.
- Non-standard schedule. The role requires flexibility to collaborate across time zones. This may occasionally include early/late meetings depending on customer and team needs.
- US Eastern Time (ET) collaboration. This role requires regular overlap with US East Coast (ET) working hours. You must be comfortable running meetings, follow-ups, and execution in that time zone.
- Zero slow offboarding. We run lean and fast. When the fit isnβt there, we act quickly: employment may be ended within a day and access is removed immediately.
Application requirement: short intro video (required):
Please include a short self-introduction video (2β5 minutes). You can add the link directly to your resume or submit it through the hiring platform in any available way (YouTube, Loom, Google Drive, or similar).
- No need for a polished production, a simple smartphone recording is perfectly fine.
- This does not replace live conversations, it only helps us speed up the first screening and understand your communication style and motivation.
- In the video, please cover:
- Who you are and 2β3 measurable outcomes you delivered in recent roles
- Why you are applying for this role at Graphio.ai
- Why you are leaving or have left your previous role
- Your view on how a high-ownership startup team should operate (pace, ownership, communication, and work-life balance expectations)
- Applications without the video may not be reviewed.
Final note:
Graphio.ai is not a 9-to-5 corporate environment. We move fast, operate with high ownership, and expect proactive execution without micromanagement. Graphio.ai is a strong fit for people who actively seek challenges for personal growth - especially those who want to build their own company one day and see this as a place to learn how high-performing startups execute.
