Middle/ Senior Python Engineer

About The Role
Build and evolve Python backend services and event-driven applications on AWS serverless infrastructure. You will own features from design through production, shape engineering standards, and mentor teammates while using AI-assisted development to accelerate delivery. This role combines hands-on coding, cloud architecture, quality ownership, and technical leadership.
Responsibilities
Design, develop, and maintain event-driven microservices and AWS Lambda functions using Python 3.12, Poetry, Pydantic, and AWS Lambda Powertools.
Build reliable asynchronous integrations across Amazon SQS, EventBridge, and Amazon MSK, including error handling, retries, and idempotency.
Model, query, and optimize application data in Amazon DocumentDB while maintaining data integrity and service performance.
Own features throughout their lifecycle, from technical design and implementation to testing, deployment, monitoring, and production support.
Create unit, integration, and BDD test coverage using pytest and behave, applying SOLID, KISS, DRY, and maintainable design patterns.
Provision AWS infrastructure with Terraform and maintain GitLab CI/CD pipelines, quality checks, hooks, and automated deployments.
Establish observability through structured logging, metrics, distributed tracing, dashboards, and alarms in Amazon CloudWatch.
Review code, mentor engineers, and use GitHub Copilot, reusable instructions, agents, and MCP integrations responsibly to improve delivery.
Requirements
5+ years of professional Python development experience, including strong knowledge of Python 3 and modern packaging practices such as Poetry.
Hands-on experience building production services with AWS Lambda and other serverless AWS technologies.
Strong understanding of event-driven architecture and messaging with SQS, EventBridge, Kafka, or Amazon MSK.
Experience with document databases, ideally Amazon DocumentDB or MongoDB-compatible technologies.
Practical knowledge of automated testing with pytest, integration testing, and BDD frameworks such as behave.
Experience provisioning cloud infrastructure with Terraform and maintaining GitLab CI/CD pipelines.
Ability to implement production observability using structured logs, metrics, traces, dashboards, and alarms.
Practical experience using AI coding assistants, agent workflows, or MCP integrations, with disciplined review of AI-generated code.
Strong ownership, code-review, communication, and mentoring skills, with a focus on secure and maintainable engineering.
SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.

Work arrangement
Yes