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: 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: Tbilisi, Georgia
Workplace: hybrid
We are looking for a Senior Data Project Manager to join inDrive's Data Platform. You will work in close partnership with the Engineering Managers of two core teams, Data Ops and Data Delivery, and coordinate projects that span multiple data platform teams: for example, onboarding data from external partners and orchestrating its downstream transformation into analytics-ready data marts.
Key Responsibilities
Coordinate cross-functional Data Platform (DWH) initiatives end-to-end, from source-system integration through the warehouse to analytical data marts
Act as the single point of accountability for initiative outcomes, ensuring value delivery within expected timeframes
Drive projects that cut across several teams, e.g. partner data ingestion followed by transformation and modeling, aligning scope, sequencing, and ownership between Data Ops, Data Delivery, and adjacent teams
Work in tandem with the Engineering Managers of Data Ops and Data Delivery on planning, capacity, and execution; participate in the operational management of the teams
Own project and initiative schedules: identify risks, dependencies, and potential slippage early, and communicate them promptly to all stakeholders
Manage priorities across product-driven requests from internal data consumers and long-term platform investments (reliability, data quality, governance, security)
Build a process for continuous improvement of team metrics: delivery performance, quality, engagement, and team maturity
Facilitate project- and program-level events (planning, syncs, retros, stakeholder reviews)
Translate between business and technical teams, keeping internal consumers, engineering, and leadership aligned
Skills, Knowledge and Expertise
3+ years of project or program management experience in Data Platform, Data Warehousing (DWH), or Analytics environments
Demonstrated success managing complex initiatives with multiple stakeholders, teams, and moving parts
Solid command of modern goal-setting and project management tools
Exceptional communication and stakeholder alignment skills: able to translate between business and technical audiences
Highly organized, with strong prioritization, risk management, and accountability-driving skills
Strong systems thinker; brings clarity and structure to ambiguity
Nice to have
Hands-on experience in Data Platform / Data Warehouse ecosystems: understanding of data pipelines, ODS-to-data-mart layering, streaming and batch delivery, data governance
Experience in high-growth consumer tech
Familiarity with modern data stack tooling (dbt, Airflow, Kafka, BigQuery or similar cloud DWH)
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 70 100 EUR gross
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: 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.
🧩 Требования: глубокие знания SQL и умение работать с планами запросов, опыт эксплуатации ClickHouse, Kafka и Kubernetes, владение Java, практический опыт создания DWH и Data Lake, опыт построения и развития высоконагруженных систем;
Location: Lisbon, Portugal
Joom
is a global cross-border marketplace where millions can find anything they want at fair prices. Joom helps consumers to make shopping easy and entertaining and provides access to interesting and unique goods from around the world.
Joom is one of the key businesses of Joom Group, an international group of tech-centric group of e-commerce companies founded in 2016 in Latvia. Joom also includes other businesses: JoomPro, the first and only end-to-end cross-border B2B marketplace; JoomPulse, an AI analytics tool for Mercado Livre sellers; and Onfy, a pharmaceutical marketplace in Germany. Joom Group has offices in Latvia, China, Germany, and Brazil, with its headquarters in Lisbon, Portugal. We work as one international team, sharing knowledge and collaborating across countries, businesses and products.
We are looking for
Lead/Senior ML developers
to join our
teams:
Search team (Lead):
will work on improving the core search algorithms, enhancing the system's understanding of user queries and the relevance of products shown in response to searches; developing new functionality to improve the user experience
Order Experience team (Senior):
developing AI/ML support: specifically, answering user questions using the full context of their orders, profile, transactions, and actions within the service, along with automating refunds
Tech stack: Go, Python, Scala, Spark, modern LLMs, PyTorch, Docker, Kubernetes, Airflow, MongoDB, Cassandra, Kafka, Jenkins
Requirements
Strong algorithmic skills: knowledge of fundamental algorithms and data structures, as well as their implementation in standard libraries
Proficiency in any language: experience in developing and debugging distributed, high-load applications, and writing testable code
Industry experience in Machine Learning: familiarity with key modeling and training approaches (linear models, GBDT, DNN, etc.), knowledge of statistics, and end-to-end ML development experience, including raw data analysis, hypothesis formulation, model creation, experimentation, and deploying results into production
Preferred
Experience in developing recommendation or search systems
Experience training neural network models
Experience working with various data sources: Spark, Cassandra, Mongo, Kafka
Knowledge of Go
We offer
Compensation package: base salary and performance-based bonuses
Office-first: flexible hours with a possibility to work remotely 52 days per year
Care & Wellbeing: health insurance (including dental care) for employees and their children, daily meal allowance, and 100% paid sick leave
Relocation Support: full assistance for a smooth relocation for the employees and their family
AI-first approach: licenses and access to a wide range of AI tools
Team & Growth: collaboration with colleagues across Portugal, Brazil, Latvia and China, with opportunities for promotions, professional trainings, and English & Portuguese courses
Community & Engagement: annual team building activities, knowledge-sharing workshops, and a strong sense of team work
Before applying for the above position please review our Candidate Privacy Notice
here
. By responding to the vacancy, you acknowledge that you have read our Privacy notice.
Задачи:
— Разработка на Java full stack с использованием React и AWS
Требования:
— Навыки работы с Java, Kafka, AWS и React
Условия:
— Частичная занятость, 2 часа в день по будням
Задачи:
— Развертывание и оркестрация микросервисных приложений стрима в кластерах Kubernetes
— Автоматизация CI/CD пайплайнов (создание и поддержка конвейеров сборки и деплоя с использованием Groovy)
— Администрирование Kafka, PostgreSQL с помощью cloud
— Подготовка документации
Требования:
— Опыт работы на позиции DevOps/SRE от 3х лет
— Глубокие знания Kubernetes, понимание архитектуры, опыт работы с helm, абстракциями (Pod, Deployment и т.п.)
— Опыт работы с Kafka, понимание принципов работы брокера, опыт конфигурации
— Опыт администрирования PostgreSQL, знание SQL, базовое понимание оптимизации запросов и индексов
— Уверенное владение Groovy, Bash/Python
— Знание Git-систем
— Будет преимуществом: опыт работы в финтехе или банковских проектах (понимание специфики ИБ, работы с критичными финансовыми данными)
Условия:
— Удалённая работа с оформлением по ТК РФ в IT-аккредитованную компанию или ИП
— ДМС (включая стоматологию)
— Компенсация фитнеса
— Скидки на обучение английскому (Skyeng)
— Индексация заработной платы
— Современная техника
— IT-аккредитация компании
Задачи:
— Работа на платформе PlatformEco (Node.js + SQL)
— Построение интеграций с внутренними и внешними продуктами
— Участие в стратегических решениях по архитектуре
Требования:
— Высшее техническое образование (ИТ, математика, физика, кибернетика)
— Опыт разработки ИИ агентов
— 5+ лет в разработке, из них 2+ года в роли Tech Lead / Team Lead команды 4–7 разработчиков (код-ревью, менторство, декомпозиция задач, участие в найме)
— Реальный продакшн-опыт на одном из стеков: Node.js, Python, .NET, Java, SQL
— Глубокий практический опыт построения интеграций: Event-driven архитектура (Kafka / RabbitMQ / аналоги), API Gateway, маршрутизация, rate limiting, идемпотентность, retry/backoff, обработка ошибок, саги, проектирование асинхронных систем с гарантиями доставки
— Опыт работы с low-code/no-code платформами
— Опыт работы в крупной корпоративной организации (5000+ сотрудников)
— Понимание архитектурных паттернов: микросервисы, CQRS, Event Sourcing, Hexagonal Architecture, DDD
— Проактивность
— Переговорные навыки без формальной власти
— Баланс «играющий тренер / лидер»
— Устойчивость к корпоративной бюрократии
— Прозрачная коммуникация
Будет плюсом:
— Рабочее понимание RAG, LLM, MCP
— Опыт в страховой / финансовой / корпоративной среде
— Готовность развиваться в сторону AI-агентов и автономных систем
Условия:
— Условия работы не указаны
Контакт для отклика: @irinaalekseevnashi
Задачи:
— Работать на платформе PlatformEco (Node.js + SQL)
— Строить интеграции с внутренними и внешними продуктами
— Участвовать в стратегических решениях по архитектуре
Требования:
— Высшее техническое образование (ИТ, математика, физика, кибернетика), фундаментальная база критична
— Опыт разработки ии агентов
— 5+ лет в разработке, из них 2+ года в роли Tech Lead / Team Lead команды 4–7 разработчиков (код-ревью, менторство, декомпозиция задач, участие в найме)
— Реальный продакшн-опыт на одном из стеков: Node.js, Python, .NET, Java, SQL (не просто знание, а опыт написания, деплоя и поддержки)
— Глубокий практический опыт построения интеграций: Event-driven архитектура (Kafka / RabbitMQ / аналоги), API Gateway, маршрутизация, rate limiting, идемпотентность, retry/backoff, обработка ошибок, саги
— Проектирование асинхронных систем с гарантиями доставки
— Опыт работы с low-code/no-code платформами, способность быстро адаптироваться к PlatformEco
— Опыт работы в крупной корпоративной организации (5000+ сотрудников) с бюрократией, согласованиями, ресурсными конфликтами и кросс-функциональными зависимостями
— Понимание архитектурных паттернов: микросервисы, CQRS, Event Sourcing, Hexagonal Architecture, DDD
— Проактивность, переговорные навыки без формальной власти, баланс между ролью тренера и лидера, устойчивость к корпоративной бюрократии, прозрачная коммуникация
Будет плюсом:
— Рабочее понимание RAG, LLM, MCP с практическим опытом встраивания AI-решений в корпоративный ландшафт
— Опыт в страховой, финансовой или корпоративной среде с пониманием compliance, безопасности, интеграции с legacy-системами
— Готовность развиваться в сторону AI-агентов и автономных систем
Условия:
— Локация: Россия (удалённо / гибрид)
— Зарплата обсуждается по итогам собеседования
УдалённоseniorКандидаты только из стартапов / небольших компаний не подходят - Понимание архитектурных паттернов — микросервисы, CQRS, Event Sourcing, Hexagonal Architecture, DDD
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