Screening requirements (please read first):
- Non-negotiable: hands-on experience building or supporting production back-end systems for process mining or task mining and ML/AI-driven workflow analysis (pipelines, workflow reconstruction, model-serving integration, evaluation/monitoring, scalable APIs).
- 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 AI Backend Engineer to design, build, and scale the core systems behind Graphio.aiβs workflow intelligence platform.
Graphio.ai connects to customer systems, ingests large volumes of event-based metadata, reconstructs real business workflows, and applies machine learning to discover ideal process paths (golden paths), detect anomalies, and surface insights.
This is a hands-on senior role for someone who is equally strong in:
- backend & distributed systems
- data-intensive architectures
- applied machine learning
- experimentation & research
- production-grade reliability
Our core stack: Python, C# (.NET Core / ASP.NET Core), MongoDB, ClickHouse, RabbitMQ.
We are looking for an engineer who deeply understands system architecture, can reason about data at scale, and is comfortable building, training, experimenting with, and deploying ML models into production.
What You Will Do:
Backend & Systems
- Design and build backend services and APIs using Python and C# (.NET Core / ASP.NET Core).
- Architect scalable, fault-tolerant, and observable systems for data ingestion, processing, and analytics.
- Build event-driven and asynchronous pipelines using RabbitMQ.
- Design data models and storage strategies using MongoDB and ClickHouse.
- Own system performance, reliability, and scalability.
- Implement strong observability: logging, metrics, tracing, alerting.
- Troubleshoot production issues, perform root cause analysis, and implement long-term fixes.
Data & Machine Learning
- Design and implement end-to-end ML pipelines: ingestion β feature engineering β training β evaluation β deployment.
- Train and iterate on ML models for workflow discovery, anomaly detection, and pattern recognition.
- Perform feature engineering on large-scale event and metadata streams.
- Run experiments, test hypotheses, and evaluate models using offline and online metrics.
- Conduct applied research: explore new modeling approaches, algorithms, and representations.
- Build batch and near-real-time inference pipelines.
- Monitor model performance, drift, and degradation in production.
- Implement retraining strategies and versioning.
Architecture & Product Thinking
- Define service boundaries, data contracts, schemas, and interfaces.
- Design for multi-tenancy, security, and compliance.
- Make pragmatic architectural decisions balancing speed, quality, and scale.
- Work closely with Product, ML, and Engineering to ship in small, measurable increments.
- Influence the technical direction of the platform.
Required Qualifications:
- 6+ years of experience in backend or systems engineering.
- Strong experience with Python and C# (.NET Core / ASP.NET Core).
- Experience building data-intensive systems (event ingestion, pipelines, analytics).
- Hands-on experience with machine learning:
- training models
- feature engineering
- experimentation
- evaluation
- Strong understanding of production ML systems (not just notebooks).
- Experience with MongoDB, ClickHouse, or similar databases.
- Experience with message brokers (RabbitMQ or similar).
- Strong understanding of distributed systems concepts:
- idempotency
- retries
- backpressure
- eventual consistency
- failure modes
- Strong analytical and problem-solving skills.
- High ownership mindset.
Nice to Have:
- Experience with workflow analytics, process mining, or event-based systems.
- Experience with time-series or behavioral modeling.
- Experience with large-scale experimentation platforms.
- Familiarity with MLOps practices.
- Experience with cost optimization for data & ML workloads.
- Experience with Kubernetes and cloud infrastructure.
Why This Role Is Special:
This is not a typical backend role.
This is not a typical ML role.
You will be building a real AI system, not demos:
- messy real-world data
- real customers
- real scale
- real constraints
- real impact
If you like working at the intersection of systems, data, and intelligence, this role is for you.
What we offer:
- A senior role owning core backend systems behind an AI/ML product with clear, measurable customer impact.
- Direct collaboration with Machine Learning Engineers to bring models into production with reliability and speed.
- Real-world data engineering problems: metadata ingestion, workflow reconstruction, and scalable reporting/alerting.
- Fast iteration, low bureaucracy, and high trust - you ship and see results quickly.
- Remote-friendly team with a simple setup and strong standards.
- Competitive compensation and room to grow as the company scales.
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.
- 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.
