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Required Backend Software Engineer
As part of the role you will have the opportunity to:
Research, design, maintain and develop core data infrastructure components
Analyze and optimize system performance, scalability, reliability, and data quality across a rich technology stack (Apache Kafka, Airflow, Storm, SQL/NoSQL databases)
Architect, design, and implement robust, performant distributed data systems (streaming and batch processing).
Collaborate with cross-functional teams to integrate data pipelines with AI/ML workflows and production monitoring systems.
Work in a fast-paced startup environment, managing multiple priorities while maintaining high code quality and operational excellence.

Required Backend Software Engineer- Platform
As part of the role you will have the opportunity to:
Be part of team responsible for designing and implementing our next generation on-premise component that facilitates communication with our customer's IoT devices - a.k.a the native connector
Help develop & maintain the underlying infrastructure that enables scalable , cost-efficient & secure communication between our cloud-native platform and the Network components & IoT devices that reside on-premise
Research & develop features that allow remote management of components that reside on premise
Help develop & maintain our IoT agent-based embedded software solution that is deployed directly onto the IoT edge devices
Research & develop integration with various external 3rd party solutions in a cloud-to-cloud and cloud-to-on-premise formations using a variety of APIs, including REST, SDKs, and other network protocols
Develop new backend services in micro-service architecture and cloud-native best practices
Guide and mentor team members
Troubleshoot and resolve technical issues, ensuring seamless operation of our services & integrations.

Required Senior Backend Engineer
As part of the role you will have the opportunity to:
Research, design, maintain and develop core data infrastructure components
Analyze and optimize system performance, scalability, reliability, and data quality across a rich technology stack (Apache Kafka, Airflow, Storm, SQL/NoSQL databases)
Architect, design, and implement robust, performant distributed data systems (streaming and batch processing).
Collaborate with cross-functional teams to integrate data pipelines with AI/ML workflows and production monitoring systems.
Mentor and guide junior engineers, defining technical best practices and driving continuous improvements.
Work in a fast-paced startup environment, managing multiple priorities while maintaining high code quality and operational excellence.

We are seeking an experienced and visionary Data Scientist to join our dynamic technology organization. The successful candidate will be a part of a team of talented data scientists, driving innovation and delivering business value through advanced machine learning techniques and Generative AI solutions. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge data science methodologies, and a passion for continuous learning and development.
Responsibilities:
Gradient boosting techniques (e.g., XGBoost, LightGBM, CatBoost) are used to enhance predictive accuracy and model robustness.
Drive the exploration and integration of Generative AI applications, including Large Language Models (LLMs), to create innovative solutions for our products and services.
Collaborate with cross-functional teams (engineering, product, business) to translate business requirements into actionable data science projects.
Establish best practices for model development, validation, deployment, and monitoring in production environments.
Promote a data-driven culture, encouraging experimentation, sharing of knowledge, and adoption of state-of-the-art technologies.
Communicate project progress, insights, and results to stakeholders at all levels of the organization. Design, implement, and optimize classic machine learning models to solve complex business problems.

We are looking for a .NET developer to join our fast-growing Acquiring dev team. You will report to the ACQ Integration Team Leader and play a key role in enhancing the Acquiring system by developing innovative new features, contributing to our teams ongoing success and growth.
Responsibilities:
Participate in all aspects of software development, including designing, hands-on coding, implementing, debugging, deployment, and troubleshooting
Accountable for overseeing the complete lifecycle of new product features and components from inception to deployment
Provide mentorship for other team members
Conduct code reviews
Be a source of knowledge for the team members regarding the technical and business aspects of the daily work
Assist the team leader in any way that is required, including leading feature development and providing guidance for other team members
Define and enforce coding standards.

Required QA Automation Engineer
Your Mission:
The QA Automation Engineer will help to continuously improve the quality, reliability and end-user experience of various solutions delivered by our development team. Also, you will help efficiently deliver high-quality solutions to end users through the use of modern quality methodologies and test automation technologies combined with a streamlined release process. The individual must be forward-thinking and share in a common vision of quality, integrity and efficiency.
Responsibilities:
Define, write, maintain & perform manual & automated tests of multiple APIs, UIs & Web services for functionality, correctness and reliability
Maintain, expand and create automation solutions
Create, maintain and execute test, bug, story & other sprint board items in Azure DevOps
Analyze and understand functional and technical requirements to devise Test cases/Test scenarios that fully meets the testing scope to satisfy business/user/system requirements
Ensure prerequisites for testing are fully prepared, test data and test environment setup/configurations
Identify and log bugs during the Software Development life cycle till release to Production
Perform root cause analysis of the bugs and collaborate with the development team to resolve and test them
Work closely with the Support team to investigate and test customer and/or production issues.
Work with your lead on improving QA processes and practices and adhering to them to ensure that quality assurance standards are met.

We are looking for a Product Data Director to lead our global product data strategy and governance. In this role, you will own the vision, implementation, and continuous improvement of how data is captured, structured, and leveraged across our product ecosystem. Youll partner closely with Product, Engineering, BI, and Operations teams to ensure data excellence, enable data-driven decision-making, and unlock insights that enhance our products, customer experience, and business growth.
Responsibilities:
Develop and execute a comprehensive product data strategy aligned with our business goals.
Define and own data standards, taxonomy, and governance frameworks across all product lines.
Partner with Product, BI, and Engineering to design scalable data models and infrastructure supporting product analytics, reporting, and performance tracking.
Lead a cross-functional data excellence initiative, ensuring high-quality, accurate, and consistent data.
Work with product managers to embed data-driven decision-making in product planning, experimentation, and optimization processes.
Oversee the implementation of data instrumentation and tracking for new product launches.
Collaborate with the Analytics and Data Engineering teams to ensure data availability and reliability across systems.

We are always looking for exceptional talent to join us on the journey!
Your Mission:
As an MLOps Engineer, your mission is to design, build, and operate the platforms that power our machine learning and generative AI products spanning real-time use cases such as large-scale fraud scoring, MCP & agentic workflows support. Youll create reliable CI/CD for models and Agents, robust data/feature pipelines, secure model serving, and comprehensive observability. You will also support our agentic AI ecosystem and Model Context Protocol (MCP) services so that models can safely use tools, data, and actions across.
You will partner closely with Data Scientists, Data/Platform Engineers, Product, and SRE to ensure every model from classic ML to LLM/RAG agents moves from prototype to production with strong reliability, governance, cost efficiency, and measurable business impact.
Responsibilities:
Operate & Develop ML/LLM platforms on Kubernetes + cloud (Azure; AWS/GCP ok) with Docker, Terraform, and other relevant tools
Manage object storage, GPUs, and autoscaling for training & low-latency model serving
Manage cloud environment, networking, service mesh, secrets, and policies to meet PCI-DSS and data-residency requirements
Build end-to-end CI/CD for models/agents/MCP tooling (versioning, tests, approvals)
Deliver real-time fraud/risk scoring & agent signals under strict latency SLOs.
Maintain MCP servers/clients: tool/resource definitions, versioning, quotas, isolation, access controls
Integrate agents with microservices, event streams, and rule engines; provide SLAs, tracing, and on-call runbooks
Measure operational metrics of ML/LLM (latency, throughput, cost, tokens, tool success, safety events)
Enforce governance: RBAC/ABAC, row-level security, encryption, PII/secrets management, audit trails.
Partner with DS on packaging (wheels/conda/containers), feature contracts, and reproducible experiments.
lead incident response and post-mortems.
Drive FinOps: right-sizing, GPU utilization, batching/caching, budget alerts.

We are seeking an experienced and visionary Data Science Team Lead to join our dynamic technology organization. The successful candidate will lead a team of talented data scientists, driving innovation and delivering business value through advanced machine learning techniques and Generative AI solutions. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge data science methodologies, exceptional leadership skills, and a passion for continuous learning and development.
Responsibilities:
Lead, mentor, and develop a team of data scientists both methodologically and technically to deliver high-impact projects aligned with our business objectives.
Design, implement, and optimize classic machine learning models to solve complex business problems.
Apply gradient boosting techniques (e.g., XGBoost, LightGBM, CatBoost) to enhance predictive accuracy and model robustness.
Drive the exploration and integration of Generative AI applications, including Large Language Models (LLMs) to create innovative solutions for our products and services.
Collaborate with cross-functional teams (engineering, product, business) to translate business requirements into actionable data science projects.
Establish best practices for model development, validation, deployment, and monitoring in production environments.
Promote a data-driven culture, encouraging experimentation, sharing of knowledge, and adoption of state-of-the-art technologies.
Communicate project progress, insights, and results to stakeholders at all levels of the organization.