Python Developer with AI and SDET

Requirements:

• Strong proficiency in Python programming and object-oriented design, with extensive experience building automation frameworks and maintainable test solutions.
• Strong knowledge of software development and testing methodologies, including unit, integration, system, regression, and end-to-end testing.
• Hands-on experience with testing frameworks such as PyTest, Robot Framework, Selenium, Playwright, or equivalent, and API testing tools such as REST Assured, Requests, or Postman.
• Experience designing and implementing CI/CD pipelines with Jenkins, GitHub Actions, GitLab CI, Azure DevOps, or similar platforms.
• Understanding of AI and machine learning concepts, model validation, and testing AI applications.
• Experience with RESTful services, microservices, databases, and distributed systems; proficiency in SQL and data validation across relational or NoSQL databases.
• Familiarity with Git-based version control and collaborative development workflows.
• Ability to analyze complex technical issues and conduct root-cause analysis; strong communication, collaboration, problem-solving, and documentation skills.
• Strong understanding of Agile and Scrum methodologies.
• Preferred: Experience developing AI-powered applications or integrating machine learning models, and knowledge of large language models, prompt engineering, retrieval-augmented generation, vector databases, and generative AI.
• Preferred: Experience with AI/ML frameworks such as TensorFlow, PyTorch, scikit-learn, or Hugging Face, and evaluating AI systems for accuracy, reliability, bias, robustness, security, and performance.
• Preferred: Familiarity with AWS, Azure, or Google Cloud; Docker, Kubernetes, infrastructure automation, and cloud-native architectures.
• Preferred: Experience in performance, load, stress, and scalability testing; event-driven systems, message brokers, asynchronous processing, observability, logging, metrics, and distributed tracing.
• Preferred: Exposure to secure software development and application security testing, and experience mentoring engineers or contributing to technical strategy and framework architecture.
• Additional assets include AI/ML-powered test automation; model monitoring, observability, and governance; knowledge of computer vision, NLP, recommendation systems, or predictive modeling; synthetic test data generation and data quality validation; open-source or reusable automation contributions; relevant certifications; experience in regulated, enterprise, or large-scale environments; and familiarity with behavior-driven development and specification-by-example.
• Strong interest in emerging technologies and applying AI to software engineering.

Responsibilities:

• Design, develop, and maintain scalable Python applications and automation solutions.
• Build and improve automated test frameworks for functional, integration, regression, API, performance, and end-to-end testing.
• Develop test strategies, plans, cases, and quality metrics.
• Integrate AI and machine learning capabilities into applications and testing processes.
• Explore generative AI, natural language processing, predictive analytics, and intelligent automation to improve engineering efficiency.
• Create AI-assisted testing solutions for test generation, defect prediction, test optimization, and root-cause analysis.
• Develop and maintain API, UI, service-level, and data-validation automation.
• Work with machine learning models, data pipelines, and AI services to support intelligent product capabilities.
• Partner with software engineers to identify quality risks and ensure testability, reliability, scalability, and maintainability.
• Integrate automated tests into CI/CD pipelines and support continuous testing.
• Troubleshoot application and automation issues across development, testing, and production environments.
• Review code, test scripts, technical designs, and implementation approaches.
• Monitor test results, analyze failures, and provide actionable recommendations.
• Contribute to engineering standards, reusable frameworks, documentation, and best practices.
• Participate in Agile ceremonies, technical discussions, sprint planning, and release activities.
• Promote quality engineering practices throughout the software development lifecycle.

Technologies:

• AI
• API
• AWS
• Azure
• Blockchain
• CI/CD
• Cloud
• Computer Vision
• DevOps
• Docker
• Git
• GitHub
• GitLab
• Support
• Jenkins
• Kubernetes
• Machine Learning
• Mobile
• NoSQL
• Playwright
• Postman
• PyTorch
• Python
• REST
• Robot Framework
• SQL
• Security
• Selenium
• TensorFlow
• microservices
• pytest
• UX UI Design

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We are Synechron, a global consulting firm using digital innovation and technology to help transform businesses. Our work spans AI, consulting, digital, cloud and DevOps, data, and software engineering for financial services and technology clients. Through our FinLabs, we develop solutions in areas including AI, blockchain, data science, digital underwriting, and mobile applications. We have more than 17,000 employees and 58 offices across 22 countries, and have received multiple employer awards. We are hiring a Python Developer – SDET & AI for a high-performing engineering team building intelligent, reliable, and scalable software. The role brings together Python development, quality engineering, test automation, AI, and machine learning, with close collaboration across engineering, product, and data science. For a role based in Chicago, Illinois, the stated base salary is $105,000–$110,000 per year, with benefits; compensation varies by geography and other factors. We offer competitive compensation and benefits, paid annual and sick leave, national holidays, parental leave, insurance, retirement savings, higher education certification support, and region-dependent commuter benefits. Our employees have access to training, personal development, more than 5,000 curated Udemy for Business courses, and coaching from FinLabs and Center of Excellence colleagues. We also offer opportunities to work abroad, projects with leading banks, financial institutions, and insurers, and a diverse, approachable global culture.

last updated 43 week of 2026