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Location: Limassol, Cyprus Workplace: hybrid We are looking for an Application Security Engineer in the AppSec team. As a Senior Application Security Engineer at inDrive, you will own whole areas of our AppSec program, from security requirements and design reviews to controls that work in production. You will work with product, platform and infrastructure teams on new architecture, AI systems and the security of our apps and services. The role fits a hands-on engineer who reviews code and architecture, leads work across several teams and makes security decisions based on data. Key Responsibilities Own one or more areas of the AppSec program end to end, including the plan, the risks and the metrics. Run security design reviews and threat modeling of new features, services and AI systems, and defend security requirements at the architecture committee. Assess the security of web, mobile and API applications and find variants of confirmed vulnerabilities across other services. Coordinate external security assessments and bug bounty findings, from triage and prioritisation with teams to fix verification. Design secure authentication and authorization between users, services and internal tools together with platform teams. Choose, pilot and tune security tools, and keep only those that pay off in real findings. Turn incidents and assessment results into lasting controls, policies and secure defaults for developers. Consult development teams on complex security issues and take shifts in AppSec duty for Critical and High incidents. Skills, Knowledge and Expertise Higher education in IT, preferably in information security. Knowledge of mobile application security on Android and iOS, client-server trust, app integrity and protection against bots and account takeover. Deep knowledge of web and API security, including authentication and authorization flaws, SSRF, injections and business logic issues, and the ability to find variants of a vulnerability class across many services. Strong understanding of identity and access, OAuth 2.0, OIDC, JWT, signing key rotation, mTLS, service-to-service authentication and SSO. Understanding of security risks of AI systems and LLM agents, such as prompt injection, excessive tool permissions and agent access to sensitive data, and practical use of AI in your own security work. Practical understanding of cloud-native infrastructure, Kubernetes, containers, API gateways and AWS. Experience in threat modeling and security design review of new features and architecture. Understanding of vulnerability management and risk, including severity, SLA, compensating controls and risk acceptance. Ability to read and review code in at least one language, preferably Golang. Track record of leading projects with two or more teams from a requirement to a verified fix, and clear written English. Experience with secrets and key management, rotation and response to credential leaks. Nice to have Knowledge of software supply chain security, dependencies, CI/CD pipelines and source control platform hardening. Experience tuning SAST, DAST and SCA tools for precision and judging a tool by noise and cost per real finding. Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Annual salary from 70 700 EUR gross. Final benefits may vary depending on the location.

Location: Cairo, Egypt Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 3+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Islamabad, Pakistan Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 3+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 3+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 3+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Help us challenge injustice by creating fair choices for millions of people across in 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Annual salary starting from 59 200 EUR gross Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid Delivery Hub is one of inDrive’s business units responsible for building and scaling the delivery product, which is rapidly expanding into new markets and adopting an AI-first approach to engineering processes. We are looking for a Tech Lead who will combine hands-on engineering with leadership responsibilities: owning team delivery and execution, defining technical direction and ensuring solution quality, as well as supporting engineers’ growth through feedback, mentoring, and regular 1:1s under the guidance of an Engineering Manager. Key Responsibilities Translate business needs into a technical strategy with measurable outcomes. Ensure alignment with the global company strategy. Identify and propose architectural and technical improvements across the product and platform, using data and trade-off analysis. Advocate, present, and defend technical solutions at the organizational level in collaboration with various stakeholders (Product, Data, Security, SRE, etc.). Participate in reviewing product & technical strategies as a subject-matter expert. Lead the process of technical research and implementation to create or improve services and systems. Write clean, effective, and maintainable code based on company standards. Participate in improving company-wide code and review standards. Take ownership of and improve the Android development lifecycle. Help engineers grow and increase their productivity. Create effective processes for knowledge sharing and collaborative work. Increase the re-use of best practices across teams. Lead task decomposition; mentor engineers and contribute to engineering guidelines. Skills, Knowledge and Expertise 6+ years of commercial Android development; expert in Kotlin and modern Android APIs. Hands-on experience with Retrofit/OkHttp, Coroutines/Flow (plus RxJava for legacy), Jetpack (Compose, WorkManager), Google Maps, FCM, and Gradle. Proven experience with CI/CD (GitHub Actions/GitLab CI), feature flags, and large-scale A/B experimentation. Strong grasp of offline storage, concurrency, performance tuning, and network debugging. Practical expertise in Clean Architecture and mainstream patterns (MVI/MVVM/MVP) applied in production. Deep understanding of client-server interaction and how to make it efficient. Knowledge of specific features and limitations for various use cases. Proven record of mentoring and technical leadership, shaping processes, and raising engineering quality across teams. Strong grasp of backend-service principles, API design, networking, concurrency, and performance optimization. Experience setting up telemetry, dashboards, and automated alerts for production systems; risk assessment and mitigation. Exceptional communication, strategic thinking, and influence; able to drive alignment across multiple teams. AI-first mindset and readiness to adopt AI tools in engineering processes. Real backend development experience is a strong plus. Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid inDrive is a global technology company building products used by millions of people around the world. We are looking for a Senior DevOps Engineer to join our Market Intelligence team and help build and maintain reliable, scalable, and efficient infrastructure for data-driven products. In this role, you will work closely with development and data teams, improve CI/CD processes, automate infrastructure and deployments, and ensure the stability and scalability of our systems across different environments Key Responsibilities Building a geo-distributed infrastructure, ensuring maximum performance and reliability of our services Participation in the life cycle of projects at all stages, including the design and development of services, resource planning and maintenance Improving processes related to system maintenance (fault tolerance, scaling, postmortems, finding and eliminating bottlenecks) Automation of build, test and application delivery processes Development of services and infrastructure management tools Taking part in creation of PaaS platform On-call duty Skills, Knowledge and Expertise Deep knowledge and understanding of Linux OS (Ubuntu, Amazon Linux) Deep knowledge of Docker / Containerd containerization technologies Experience in building CI/CD Pipelines Experience in using Ansible / Saltstack and writing roles / playbooks / states / pillars Strong understanding of command of Git Ability to independently decompose tasks and bring them to the end Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Annual salary starting from 59 200 EUR gross. Final benefits may vary depending on the location.

Location: Cairo, Egypt Workplace: hybrid The Grocery Team is responsible for building and evolving the customer experience for grocery delivery — from discovering stores and products to browsing the catalog, managing the cart, and completing checkout. We’re looking for a QA Engineer to join our team Key Responsibilities Test the full grocery customer journey, including store selection, catalog, search, product details, cart, checkout, payment, and order creation. Validate prices, discounts, inventory, product availability, and store-specific assortment across different locations and partners. Test grocery-specific scenarios such as weighted products, substitutions, unavailable items, quantity limits, and minimum order values. Test integrations between the storefront and catalog, pricing, inventory, order, payment, and delivery services, as well as external grocery partners. Validate fallback and degradation scenarios when a partner or internal service is unavailable. Ensure consistent behavior across mobile applications, WebView, and backend APIs. Develop and maintain automated tests and contribute to API, integration, and end-to-end test coverage. Participate in requirements reviews, test strategy, release validation, and investigation of production issues, taking ownership of quality throughout the product lifecycle. Skills, Knowledge and Expertise Strong experience in functional, integration, API, and end-to-end testing across the full customer journey: catalog, search, PDP, cart, checkout, payment, and order creation. Experience testing dynamic pricing, inventory, discounts, product availability, quantity limits, and minimum order value. Experience testing location- or store-specific assortment, including warehouse and geo-based availability. Good understanding of grocery-specific scenarios, such as weighted products, substitutions, unavailable items, and partial orders. Experience testing integrations with catalog, pricing, inventory, order, payment, and delivery services, including third-party partner APIs. Strong understanding of microservices, event-driven and asynchronous architectures, including retries, timeouts, idempotency, duplicate events, and eventual consistency. Experience with REST and/or gRPC APIs and automated API testing; familiarity with tools such as Postman. Experience creating and maintaining automated tests using frameworks such as Playwright, Cypress, Appium, or similar. Ability to investigate issues using logs, metrics, traces, databases, and message queues; experience with tools such as Grafana, CloudWatch, Kibana, Kafka, and SQL. Experience working with CI/CD pipelines, Docker, and AWS-based environments. Ability to validate consistency across mobile applications, WebView, backend APIs, and distributed services, and troubleshoot partial failures and partner/service outages. Experience contributing to test strategy, requirements reviews, release validation, and production issue analysis, with a focus on business risks and product quality throughout the entire development lifecycle. Nice to have: experience with grocery/e-commerce products, mobile testing, contract testing, external partner integrations, performance/load/resilience testing, feature flags, A/B testing, and product metrics such as conversion, add-to-cart rate, checkout completion, error rate, and latency. Conditions & Benefits Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Islamabad, Pakistan Workplace: hybrid The Grocery Team is responsible for building and evolving the customer experience for grocery delivery — from discovering stores and products to browsing the catalog, managing the cart, and completing checkout. We’re looking for a QA Engineer to join our team Key Responsibilities Test the full grocery customer journey, including store selection, catalog, search, product details, cart, checkout, payment, and order creation. Validate prices, discounts, inventory, product availability, and store-specific assortment across different locations and partners. Test grocery-specific scenarios such as weighted products, substitutions, unavailable items, quantity limits, and minimum order values. Test integrations between the storefront and catalog, pricing, inventory, order, payment, and delivery services, as well as external grocery partners. Validate fallback and degradation scenarios when a partner or internal service is unavailable. Ensure consistent behavior across mobile applications, WebView, and backend APIs. Develop and maintain automated tests and contribute to API, integration, and end-to-end test coverage. Participate in requirements reviews, test strategy, release validation, and investigation of production issues, taking ownership of quality throughout the product lifecycle. Skills, Knowledge and Expertise Strong experience in functional, integration, API, and end-to-end testing across the full customer journey: catalog, search, PDP, cart, checkout, payment, and order creation. Experience testing dynamic pricing, inventory, discounts, product availability, quantity limits, and minimum order value. Experience testing location- or store-specific assortment, including warehouse and geo-based availability. Good understanding of grocery-specific scenarios, such as weighted products, substitutions, unavailable items, and partial orders. Experience testing integrations with catalog, pricing, inventory, order, payment, and delivery services, including third-party partner APIs. Strong understanding of microservices, event-driven and asynchronous architectures, including retries, timeouts, idempotency, duplicate events, and eventual consistency. Experience with REST and/or gRPC APIs and automated API testing; familiarity with tools such as Postman. Experience creating and maintaining automated tests using frameworks such as Playwright, Cypress, Appium, or similar. Ability to investigate issues using logs, metrics, traces, databases, and message queues; experience with tools such as Grafana, CloudWatch, Kibana, Kafka, and SQL. Experience working with CI/CD pipelines, Docker, and AWS-based environments. Ability to validate consistency across mobile applications, WebView, backend APIs, and distributed services, and troubleshoot partial failures and partner/service outages. Experience contributing to test strategy, requirements reviews, release validation, and production issue analysis, with a focus on business risks and product quality throughout the entire development lifecycle. Nice to have: experience with grocery/e-commerce products, mobile testing, contract testing, external partner integrations, performance/load/resilience testing, feature flags, A/B testing, and product metrics such as conversion, add-to-cart rate, checkout completion, error rate, and latency. Conditions & Benefits Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid Join the Storefront Team and help build the core customer-facing experience of our marketplace - from discovering partners and browsing product catalogs to product details, cart, and checkout. You’ll work on scalable backend solutions that provide a seamless experience across different partners while improving performance, personalization, conversion, and enabling the rapid integration of new partners. Location: Georgia (country) 🇬🇪 Key Responsibilities Developing backend services for a grocery storefront, including catalog, categories, search, PDP, cart, and checkout. Working with large catalogs and assortments that depend on a specific store, warehouse, or user location. Handling frequently changing prices, inventory, discounts, and product availability. Validating the cart before checkout, including prices, availability, quantity limits, minimum order value, and store restrictions. Supporting grocery-specific scenarios such as weighted products, unavailable items, and substitutions. Integrating with catalog, pricing, inventory, order, payment, and delivery services. Onboarding grocery partners with different APIs and data models. Ensuring low latency, high availability, and resilience of customer-facing flows. Skills, Knowledge and Expertise Mandatory: proven experience in the grocery 5+ years of commercial backend engineering. With experience solving complex problems in high-load environments Strong knowledge of Go programming language. Knows and has applied advanced features of the Go language in practice Strong SQL knowledges, including designing schemas, scaling strategies (replication, partitioning, sharding) and query optimisation for high-load environment In-depth knowledge of Redis, familiar with various data structures, and its efficient use in high-load systems Experience working with Docker, understanding CI/CD pipelines. Knows how work k8s (or analogs) and cloud infrastructure (like AWS) Experience with synchronous and asynchronous inter-service communication patterns, with a focus on reliability in high load environment Knows main microservice architecture patterns. Deep understanding of how to build efficient interactions between client and server applications, knows limitations Proven ability to design and implement a full observability strategy, including metrics, logging, dashboards, and tracing An interest in new technologies, a collaborative spirit, and a drive to continuously develop your skills Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Cairo, Egypt Workplace: hybrid We are looking for a Senior Data Engineer to join one of the Data Platform teams that works with the Marketing, Growth, partner, and financial data domains. You will be working with cutting edge cloud technologies (GCP, AWS, BigQuery, Databricks, K8s) and building a large scale data infrastructure for analytics, machine learning, and streaming/CDC data delivery. Key Responsibilities Build and operate batch and streaming ingestion into a layered BigQuery DWH (raw → ODS → data marts) using Airflow, Debezium CDC over Kafka with protobuf, Pub/Sub, and Dataflow Integrate external data sources end-to-end — marketing platforms (GA4, AppsFlyer, TikTok/Meta/Google Ads), payment providers, S3 buckets, and third-party APIs — including schema contracts, backfills, and reconciliation Engineer the data platform itself in Python: custom Airflow operators and connectors in a shared ETL framework, Kafka Connect on Strimzi (K8s), Cloud Functions, and API integrations with external providers Build CI/CD and change-management tooling for BigQuery: GitHub-based test-and-approval flows, SQL migration engines (Liquibase/Flyway/Bytebase), sandbox validation, backup and rollback Own reliability and correctness of pipelines: idempotency, deduplication, late-data handling, backfill and replay, freshness monitoring and alerting; write integration and unit tests Drive data governance and compliance: ITGC-compliant change management for BigQuery, IAM and least-privilege access, PII policy tags and DLP, Unity Catalog on Databricks, column-level lineage (OpenMetadata/Dataplex), and disaster-recovery planning Build internal data tools and platform services for agentic workflows with data — Streamlit apps, Slack bots, LLM-based agents and MCP servers that help teams find and use data Support analysts and business teams with data requests, fostering data-driven decision-making across the company Contribute to system design and architecture with the development team Skills, Knowledge and Expertise Strong practical Python: clean, well-structured, and tested code for services, tooling, and data pipelines Solid software design skills (OOP, modularity, design patterns) — we build platform tools for agentic workflows with data and plan to develop data-related backend services, so well-designed code is highly valued Experience building and operating services in a cloud environment (GCP, AWS or similar): CI/CD, containerization, monitoring and alerting Familiarity with Kubernetes and Terraform — our infrastructure runs on GCP/K8s Hands-on experience with DWH-related tasks (BigQuery or another cloud warehouse) and confident working SQL Clear communication with non-engineering stakeholders — a meaningful share of the work is data requests from analysts and business teams Demonstrated ability to take ownership of technologies or services and proactively contribute ideas to the team Nice to have Advanced SQL: complex queries, window functions, partitioning, clustering, and cost optimization Experience building reliable pipelines around CDC (e.g., Debezium): idempotency, schema evolution, backfills, and reconciliation Analytical data modeling skills: table grain, facts vs dimensions, slowly changing dimensions, and metric definitions Experience with stream processing frameworks such as Flink or Apache Beam/Dataflow Exposure to data governance and audit compliance (ITGC/SOX), Databricks Unity Catalog, or lineage/catalog tooling (OpenMetadata, Dataplex) Interest in building LLM-based agents and AI tooling for data Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid We're looking for an Infrastructure Security Engineer to secure complex multicloud infrastructure, which runs mostly on Kubernetes. You'll join the security team as a hands-on engineer who builds, not just reviews: security processes, automating checks and working side by side with a team of skilled professionals. InDrive is an AI-friendly company. We use AI tools in daily engineering work and encourage you to use them to automate security operations, speed up reviews and build better tooling. Key Responsibilities Build, maintain and evolve the security of our multicloud environment, Kubernetes clusters and CI/CD systems. Build and maintain vulnerability management processes using commercial and open-source tools, and help engineering teams drive remediation. Contribute to the architectural design of infrastructure services, bringing security expertise across the full lifecycle, from design to production. Run regular security assessments and hardening reviews, and turn findings into secure baselines and guardrails. Automate security checks and operations with code, and use AI-assisted tooling where it makes the team faster. Work with SIEM and monitoring to improve detection coverage for cloud and Kubernetes workloads. Take part in incident response for cloud and Kubernetes environments. Skills, Knowledge and Expertise 3+ years of hands-on experience in infrastructure security, including vulnerability management across cloud and on-prem environments. Strong proficiency with cloud platforms (AWS or GCP) and with Kubernetes: applying security best practices for a high-load production infrastructure. Strong knowledge of IaC tools (Terraform, Terragrunt, Ansible), GitOps (ArgoCD), and CI/CD pipeline security (e.g. GitHub Actions). Understanding of risk based approach to vulnerability management and Cybersecurity in general Automation skills in Python or Bash. Understanding of Zero Trust principles and experience securing remote access with ZTNA solutions. Experience with SIEM solutions. Good written and spoken English. Nice to have Certifications: CKS (Certified Kubernetes Security Specialist) and/or AWS Certified Security – Specialty. Experience with Kubernetes security tooling: policy engines, runtime security and network policies. Hands-on experience with AWS native security services (GuardDuty, Security Hub, IAM Access Analyzer, CloudTrail). Hands-on incident response experience in cloud or Kubernetes environments. Familiarity with secret management tools (e.g. HashiCorp Vault, AWS Secrets Manager). Experience using LLMs or AI agents to automate security workflows Why join us Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Annual salary from 80 000 EUR gross Final benefits may vary depending on the location.

Location: Cairo, Egypt Workplace: hybrid Several Backend Engineer positions are available within product teams. Each role is embedded in a single team and focuses on the development and scaling of backend solutions across the company’s product areas. Key Responsibilities Design and implement complex business logic in Golang autonomously, while ensuring high performance and system reliability. Design optimal database structures (SQL), manage indexes, and optimize query performance. Build asynchronous service interactions using Kafka. Take ownership of backend services lifecycle, including delivery, monitoring and maintaining backend services in the production environment Write clean, structured code, conduct code reviews, ensure compliance with architectural guidelines (ADR), and implement engineering best practices. Set up monitoring and alerting for your services, participate in Post-Mortem processes, identify root causes of incidents, and automate routine tasks. Share expertise with the team, participate in onboarding new members, and contribute to the development of internal libraries and tools. Proactively seek improvements in technical implementations and product solutions, striving to deliver the best possible user experience. Skills, Knowledge and Expertise 6+ years of commercial backend engineering. With experience solving complex problems in high-load environments 3+years of commercial experience with Golang. Knows and has applied advanced features of the Go language in practice Strong SQL knowledges, including designing schemas, scaling strategies (replication, partitioning, sharding) and query optimisation for high-load environment In-depth knowledge of Redis, familiar with various data structures, and its efficient use in high-load systems Experience working with Docker, understanding CI/CD pipelines. Knows how work k8s (or analogs) and cloud infrastructure (like AWS) Experience with synchronous and asynchronous inter-service communication patterns, with a focus on reliability in high load environment Knows main microservice architecture patterns. Deep understanding of how to build efficient interactions between client and server applications, knows limitations Proven ability to design and implement a full observability strategy, including metrics, logging, dashboards, and tracing An interest in new technologies, a collaborative spirit, and a drive to continuously develop your skills Conditions & Benefits Stable salary, official employment. Health insurance. Hybrid work mode and flexible schedule. Access to professional counseling services including psychological, financial, and legal support. Discount club membership. Diverse internal training programs. Partially or fully paid additional training courses. All necessary work equipment.

Location: Almaty, Kazakhstan Workplace: hybrid Several Senior Backend Engineer positions are available within product teams. Each role is embedded in a single team and focuses on the development and scaling of backend solutions across the company’s product areas. Key Responsibilities Design and implement complex business logic in Golang autonomously, while ensuring high performance and system reliability. Design optimal database structures (SQL), manage indexes, and optimize query performance. Build asynchronous service interactions using Kafka. Take ownership of backend services lifecycle, including delivery, monitoring and maintaining backend services in the production environment Write clean, structured code, conduct code reviews, ensure compliance with architectural guidelines (ADR), and implement engineering best practices. Set up monitoring and alerting for your services, participate in Post-Mortem processes, identify root causes of incidents, and automate routine tasks. Share expertise with the team, participate in onboarding new members, and contribute to the development of internal libraries and tools. Proactively seek improvements in technical implementations and product solutions, striving to deliver the best possible user experience. Skills, Knowledge and Expertise 6+ years of commercial backend engineering. With experience solving complex problems in high-load environments 4+years of commercial experience with Golang. Knows and has applied advanced features of the Go language in practice Strong SQL knowledges, including designing schemas, scaling strategies (replication, partitioning, sharding) and query optimisation for high-load environment In-depth knowledge of Redis, familiar with various data structures, and its efficient use in high-load systems Experience working with Docker, understanding CI/CD pipelines. Knows how work k8s (or analogs) and cloud infrastructure (like AWS) Experience with synchronous and asynchronous inter-service communication patterns, with a focus on reliability in high load environment Knows main microservice architecture patterns. Deep understanding of how to build efficient interactions between client and server applications, knows limitations Proven ability to design and implement a full observability strategy, including metrics, logging, dashboards, and tracing An interest in new technologies, a collaborative spirit, and a drive to continuously develop your skills Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid The QA Load team is responsible for the performance and scalability of services across their entire lifecycle — from Go/No-Go decisions before launch to working with real production traffic. We design and execute load tests, model real-world usage scenarios, identify and eliminate bottlenecks in backend systems, databases, messaging, and infrastructure, and work closely with SRE, DevOps, and product engineering teams. The role focuses on systematic performance improvement: building load-testing infrastructure, automation and CI/CD quality gates, performance analysis and experimentation, and translating technical metrics (latency, RPS, p95/p99) into clear business impact. Our goal is to make performance a core aspect of product quality and ensure the stable operation of high-load, geo-distributed systems. Key Responsibilities Performance Audits & Integration Support: Go/No-Go decisions with our stakeholder about launches services before integrating them into our ecosystem and integrations support (audit APIs, web, databases, caches, message brokers) Design&Execute Load Tests global strategy: Modeling of load testing scenarios (load, stress, soak, peak, find max tests), methodology and formation of non-functional requirements for system using k6, JMeter (DSL framework) Simulate real-world scenarios and traffic patterns to validate systems under production-like conditions (including high RPS, concurrency levels, data skew, and geo-distributed load) Load Modeling: Calculate and validate detailed load models – e.g. expected RPS, concurrent users, transaction volumes, and data distribution. Adjust these models to mirror peak and edge-case scenarios, ensuring our capacity planning is grounded in reality. Bottleneck Analysis & Fixes: Find, analyze, and fix performance bottlenecks. This includes: backend issues (CPU hotspots, memory leaks, GC pauses, thread pool exhaustion) DB inefficiencies (Aurora MySQL/RDS indexing, query locks, IOPS limits) messaging/queue back-pressure (Kafka partitioning, consumer lag, throughput limits) network constraints (latency, load balancer settings, timeouts) Work hands-on with SRE, DevOps, and Backend teams to implement optimizations and verify the improvements. Prepare for Production Traffic: Ensure services are production-ready. Drive capacity planning exercises and stress tests to determine scaling lag/limits and failure modes. Verify that services can gracefully handle traffic spikes or component failures without violating SLAs or SLOs. Help partners configure autoscaling policies for sustained performance Loadtesting Infrastructure Setup&Tuning: Set up, audit, and operate performance testing infrastructure for our services load testing automation and geo-distributed load generator to simulate production traffic Performance Analysis & Experimentation: Approach performance issues with an performance analyst/architect mindset – form hypotheses, design experiments, run tests, and draw conclusions to configuration infrastructure and fix backend code. For example, if latency is high, hypothesize the cause (e.g. database index missing), test the hypothesis, and then make a the fix. Repeat this iterative process to methodically improve system performance. Business Impact Translation: Translate technical performance insights into business risks and opportunities. For instance, demonstrate how reducing latency or improving p95 response time can increase conversion rates or GMV. Communicate these insights to both engineers and non-technical stakeholders to underline the business value of performance work. Observability & Monitoring: Utilize observability tools to monitor performance during tests. Set up dashboards and alerts in Grafana/Prometheus and other systems (e.g. New Relic, Dynatrace, Zabbix, ELK Stack, Coroot), analyze traces and logs. Use few methods to interpret results and guide troubleshooting. Performance Tooling: Build internal performance tooling in Golang: Design and maintain internal tools for automation performance testing and analysis Load as a Service for product teams: traffic generators, load managers, mocks, test stubs, data feeders, and helper services used across partner integrations. Building load test scenarios to Jmeter (DSL framework) and k6 in JavaScript. Innovate on tooling to make load tests easier to create, run, and analyze for the whole team. CI/CD Integration: Integrate performance tests into our CI/CD pipeline as QG. Automate load tests run to every new integration or code change is evaluated for performance regressions. Ensure that build pipelines can catch and flag performance drops (e.g. increased response times, higher resource usage) before changes reach production. Reporting&Communication: Prepare executive-ready performance reports for engineering teams and C-level stakeholders. Highlight key metrics (p95/p99 latency, throughput, error rates, saturation signals) and identify primary scalability bottlenecks across services, databases, caches, and messaging systems, and compare results against SLOs and capacity targets. Provide clear root-cause explanations and actionable recommendations, including performance vs cost trade-offs, to support production readiness and Go/No Go decisions. Performance Culture: Champion a culture where performance = product quality. Educate and influence teams to treat performance testing as an integral, continuous part of the development lifecycle rather than a one-time task. Share best practices and success stories, ensuring that performance considerations are baked into design, coding, and testing processes from the start. Conducting production load and traffic validation experiments with full ownership of risk assessment, blast radius control, observability, and rollback procedures. Work with geo-distributed, high-load systems (200k+ RPS) and latency-sensitive mobile flows Set up production-like performance environments in AWS Conducting and modeling load tests in production Performance analytics → hypotheses → experiments → fixes → measurable business impact (latency, conversion, GMV) Skills, Knowledge and Expertise 5+ years in Performance/SRE/Load Testing Strong programming skills in Golang/Kotlin/Java Strong k6 or JMeter DSL - Performance Testing Mastery: Hands-on expertise with modern load testing tools, especially k6 and/or JMeter (and their scripting DSL). Deep understanding of performance best practice – you know when to apply load testing vs stress testing vs soak testing, and how to interpret the results of each. Hands-on experience with AWS infrastructure on for high-load systems: EKS, EC2, Auto Scaling Groups, ALB/NLB, VPC, subnets, routing, security groups Designing and tuning autoscaling strategies for compute (KEDA/Karpenter/Cluster Autoscaler, EC2 scaling policies) Understanding network performance characteristics: latency, cross-AZ traffic, NAT/egress limits, load balancer behavior under high RPS Profiling Golang, Kafka, Redis, DB tuning experience Automation loadtesting and make QG (JVM languages and Go) SRE mindset (RED/USE, SLO, error budgets) Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid We are looking for a hands-on Risks Ops to own and evolve our core Decision-Making System (DMS) and credit processing engine. In this role, you will bridge the gap between risk management, and core engineering, leading a focused team of developers to design, build, and optimize high-throughput, low-latency decisioning engines. You will play a pivotal role in streamlining time-to-market for credit strategy changes, integrating advanced ML scoring models, and replacing legacy software with modern, scalable, in-house microservices architecture. Key Responsibilities Technical Leadership & Ownership: Take full ownership of the end-to-end Decision-Making System (DMS) lifecycle, including system architecture, deployment pipelines, production monitoring, continuous code cleanup, and performance optimization. Cross-Functional Collaboration: Partner closely with Risk Analysts and Data Scientists to translate complex business logic, risk rules, and ML scoring models (application, behavioral, fraud) into production-ready software. Team Leadership & Delivery: Implement core logic of DMS system to suit the needs of InDrive's lending vertical. Code reviews, release management, and performance evaluations while fostering an efficient, agile environment. Process Optimization: Reduce time-to-market for credit strategy updates by modernizing delivery workflows, introducing automated regression/retrospective testing, and eliminating dependencies on legacy release cycles. Architecture & System Integration: Drive the evolution of our high-volume microservices ecosystem (Golang, AWS). Integrate internal and external services (credit bureaus, collection platforms, fraud detection services) via REST APIs and event-driven pipelines. Skills, Knowledge and Expertise Fintech & Credit Decisioning Expertise: 7+ years of total backend engineering experience, with deep domain expertise in financial technology, credit conveyors, loan processing, debt collection systems, or automated decisioning engines. Risk-Ops experience: be familiar with any popular decision-engine (gorules, n8n, camunda, SAS RTDM, FICO Blaze Advisor etc…) Stack: Strong expertise in Golang / Python, and build tools (Gitlab CI), AWS-related experience will be a huge plus. Data Management: Proficiency with relational and non-relational databases (MySQL, AuroraDB, DynamoDB, GBQ). DevOps, CI/CD & Observability: Hands-on experience with modern CI/CD tools (GitLab CI, GitHub Actions), containerization (Docker), and system monitoring tools (Prometheus, Grafana). Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Annual salary from 75 600 EUR gross. Final benefits may vary depending on the location.

– Опыт коммерческой разработки от 5 лет и уверенное владение Python. – Умение проектировать и сопровождать production-сервисы: API, модели данных, очереди и фоновые задачи, тесты, метрики, логи и tracing.