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описание
Avenga is an international engineering firm helping businesses operate with AI at the core. It combines engineering expertise with AI-native thinking to turn ambitious ideas into real-world impact across industries, technologies, and markets.
задачи
Build polished, accessible, and well-tested React/TypeScript interfaces for cost and usage dashboards, connector configuration, and platform administration
Design, develop, and maintain scalable Go-based microservices and REST/gRPC APIs
Build and evolve Python connectors and collectors for AWS, Azure, GCP, LLM providers, and SaaS vendors
Extend the established connector pipeline across credential management, execution, normalisation, persistence, and presentation, following established patterns rather than introducing one-off integration approaches
Ensure every new integration follows consistent product patterns, from connector tile through creation and edit flows
Normalise vendor cost and usage data to the FOCUS standard, including AI token- and credit-based billing data
Model and persist data using SQL, Python ORMs, and Databricks where appropriate
Improve platform observability, reliability, performance, scalability, and security
Deploy and support services in AWS; work with Azure and GCP as integration targets and data sources
Use Docker, Kubernetes, CI/CD, ArgoCD, and feature flags to ship changes safely and reliably
Use AI coding tools in daily delivery while treating prompts, skills, and internal documentation as reviewable engineering artefacts
Turn repeatable work into reusable skills, agents, and documented playbooks that improve the whole team’s effectiveness
требования
5+ Years of professional software engineering experience, including delivery in a consulting, client-facing, or contract environment
Strong, recent hands-on experience building production web applications with React and TypeScript
Production backend experience with Go, including at least one year of commercial Go development
Production experience with Python, particularly for API integrations, data collection, or backend services
Proven experience integrating third-party REST APIs, including OAuth/API-key authentication, pagination, rate limiting, retries, idempotency, error handling, and partial-failure scenarios
Strong understanding of REST APIs, microservices, distributed systems, and service-to-service integration patterns
Solid SQL and data-modelling experience, including practical work with an ORM such as SQLAlchemy, Django ORM, Hibernate, or equivalent
Working knowledge of Docker, Kubernetes, CI/CD, Git, and modern code-review and testing practices
Experience working in Agile teams using Jira and Confluence as part of the normal development workflow
Confidence using AI-assisted engineering tools while critically reviewing, testing, and validating generated code
Strong written and spoken communication skills, a pragmatic problem-solving mindset, and the ability to ramp up quickly in a complex product environment
Будет плюсом: FinOps, cloud cost management, cloud billing, usage analytics, or familiarity with the FOCUS standard; IT Asset Management or software-licensing domain knowledge; experience with FlexNet Manager Suite; AWS Cost and Usage Report, Azure Cost Management, GCP billing exports, or comparable cloud billing APIs; LLM provider APIs, usage or analytics endpoints, and token- or credit-based billing models; gRPC, Protocol Buffers, Databricks, event-driven architectures, or messaging platforms; strong AWS experience, including deploying and supporting production applications; Kubernetes Jobs, ArgoCD, Helm, GitOps practices, or feature-flag platforms such as Split.io; n8n or similar workflow-automation tools, together with sound judgement about when an automation should become a supported service; observability, monitoring, distributed tracing, and production reliability practices; internal developer tooling, agent skills, MCP servers, or reusable AI-enabled engineering workflows; previous experience in a SaaS product organisation