SDET – Java/Python, Playwright, Microservices & CI/CD
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Job Summary
Synechron is seeking a Quality Engineering Developer (SDET) with 7+ years of experience to join its engineering-focused Quality Engineering team in India. This role is responsible for designing and building scalable quality engineering solutions across UI, API, integration, event-driven, and distributed system layers. The successful candidate will work closely with developers and architects to build quality into system design, automate validation across the SDLC, strengthen release readiness, and support production excellence. The role contributes to business objectives by improving software reliability, delivery confidence, system observability, and production quality across mission-critical platforms.
Software Requirements (Required and Preferred)
Required
Java and/or Python: Expert-level proficiency in Java or Python, including object-oriented programming, data structures, design patterns, and maintainable software engineering practices.
Playwright: Hands-on experience developing modern UI automation using Playwright.
API Testing: Strong experience testing REST APIs, microservices, service integrations, and distributed application interfaces.
CI/CD Platforms: Experience embedding automated quality gates into CI/CD pipelines using TeamCity, Jenkins, GitHub, or equivalent approved platforms.
SQL: Strong proficiency in SQL for backend data validation, test data management, reconciliation, and database verification.
Automation Frameworks: Proven experience designing and building scalable automation frameworks from scratch across UI, API, integration, and event-driven layers.
BDD: Practical experience implementing maintainable Behavior-Driven Development solutions.
Distributed Systems Testing: Experience validating microservices, event-driven architectures, high-availability systems, and low-latency platforms.
Performance and Reliability Testing: Experience with performance, load, stress, and resilience testing.
Observability and Production Diagnostics: Ability to use logs, metrics, traces, and production telemetry to investigate issues and guide quality strategy.
AI/GenAI Tools: Hands-on experience using AI or GenAI tools for test design, automation development, debugging, and quality engineering workflows.
AI Evaluation: Experience validating AI-generated code, test cases, automation, and technical outputs.
Prompt Engineering and Context Management: Practical experience creating effective prompts and managing context for AI-assisted engineering activities.
Spec-Driven Development (SDD): Proven experience aligning specifications, implementation, and validation through Spec-Driven Development practices.
Agents, Skills, and MCP Integrations: Experience using or developing Agents, Skills, and Model Context Protocol (MCP) integrations.
Production Quality Ownership: Experience with release certification, regression strategy, production validation, incident triage, and root-cause analysis.
Production Support: Willingness to support production releases, including participation in on-call rotations.
Preferred
Perfecto: Exposure to or experience with mobile and web application testing using Perfecto.
Agentic Engineering: Understanding of agentic approaches applied to software development or quality engineering.
JMeter: Experience with performance, load, or stress testing using JMeter.
Advanced AI-Assisted QE: Experience embedding AI-assisted quality engineering workflows safely into CI/CD pipelines.
Cloud and Platform Tools: Exposure to cloud-based environments, observability platforms, containerized systems, or distributed application infrastructure.
Test Reporting and Quality Analytics: Experience with automated test reporting, quality dashboards, release metrics, and engineering productivity measures.
Overall Responsibilities
Design, develop, and maintain scalable automation frameworks across UI, API, integration, event-driven, and distributed system layers.
Act as a quality engineering architect by influencing system design, testability, observability, reliability, and release readiness.
Embed automated quality gates into CI/CD pipelines to provide timely and actionable feedback throughout the software delivery lifecycle.
Engineer quality solutions for microservices, event-driven architectures, high-availability platforms, and low-latency systems.
Develop maintainable automated tests using Java and/or Python, Playwright, REST API tools, SQL, BDD practices, and appropriate testing frameworks.
Validate application behavior across functional, integration, regression, performance, load, stress, resilience, and production environments.
Use AI and GenAI tools to accelerate test design, automation development, debugging, test analysis, and quality engineering activities.
Evaluate AI-generated code, tests, prompts, and technical outputs to confirm accuracy, reliability, maintainability, security, and suitability for use.
Apply prompt engineering, context management, responsible AI practices, and verification controls to AI-assisted QE workflows.
Apply Spec-Driven Development to maintain alignment between specifications, implementation, automated validation, and expected outcomes.
Use and develop Agents, Skills, and MCP integrations to support safe and effective engineering and quality workflows.
Analyze logs, metrics, traces, and production telemetry to identify quality risks, investigate failures, and guide testing priorities.
Own end-to-end production quality activities, including release certification, regression strategy, production validation, incident triage, and root-cause analysis.
Collaborate with developers, architects, product teams, operations, and other stakeholders to resolve technical issues and improve delivery outcomes.
Support production releases and participate in on-call rotations as required.
Maintain automation code, test documentation, quality reports, release evidence, technical standards, and operational procedures.
Improve engineering efficiency by reusing automation components, reducing redundant test execution, and considering responsible use of compute and infrastructure resources.
Technical Skills (By Category)
Programming Languages
Essential
Expert-level Java and/or Python programming.
Strong understanding of object-oriented programming, data structures, design patterns, modular design, exception handling, and maintainable code practices.
Ability to build automation frameworks and test utilities from the ground up.
Experience writing reliable, readable, reusable, and testable automation code.
Preferred
Experience with additional scripting or programming languages used for test automation, system integration, or operational support.
Experience developing utilities for test data generation, service virtualization, reporting, or quality analytics.
Databases and Data Management
Essential
Strong SQL proficiency for data validation, backend verification, reconciliation, test data preparation, and defect investigation.
Ability to validate data across application services, databases, APIs, event streams, and integrated systems.
Understanding of data consistency, integrity, completeness, transaction behavior, and data lifecycle considerations.
Experience analyzing database results and identifying discrepancies between expected and actual system behavior.
Preferred
Experience validating data in distributed, high-volume, or event-driven systems.
Exposure to database performance testing, data quality dashboards, data profiling, or test data management tools.
Experience working with multiple database technologies.
Cloud Technologies
Essential
Understanding of distributed application deployment, service availability, scalability, and reliability in modern infrastructure environments.
Ability to support testing and quality validation across development, integration, staging, and production-like environments.
Understanding of CI/CD, service dependencies, deployment configurations, and environment-specific test execution.
Preferred
Experience testing applications deployed on cloud platforms.
Exposure to containerized applications, orchestration platforms, cloud observability, and infrastructure automation.
Experience validating cloud-native microservices, event-driven systems, or highly available platforms.
Frameworks and Libraries
Essential
Playwright for modern UI automation.
REST API and integration testing frameworks or utilities.
Frameworks supporting Java and/or Python-based automation development.
Practical and maintainable BDD implementations.
Frameworks or tools for performance, load, stress, and resilience testing.
Tools or utilities for validating logs, metrics, traces, and production telemetry.
Preferred
JMeter for performance and load testing.
Perfecto for mobile or web application testing.
Frameworks supporting contract testing, service virtualization, event validation, or distributed systems testing.
Libraries for AI-assisted test generation, evaluation, automation, or debugging.
Development Tools and Methodologies
Essential
Experience building automation frameworks from scratch and scaling them for enterprise use.
TeamCity, Jenkins, GitHub, or equivalent CI/CD platforms with automated quality gates.
Git or equivalent source control practices, including branching, merging, pull requests, and code review.
Spec-Driven Development experience.
Experience integrating automated tests into the SDLC and release process.
Experience with functional, integration, regression, performance, load, stress, resilience, and production validation testing.
Experience with release certification, incident triage, root-cause analysis, and on-call support.
Hands-on use of AI/GenAI tools for test design, automation coding, debugging, and quality analysis.
Experience evaluating AI-generated code and tests and verifying AI outputs before use.
Experience with prompt engineering, context management, Agents, Skills, and MCP integrations.
Understanding of responsible AI usage and safe integration of AI-assisted QE workflows into CI/CD.
Preferred
Experience with Agile/Scrum delivery practices and cross-functional engineering teams.
Exposure to test reporting, quality dashboards, release metrics, and engineering productivity analysis.
Experience contributing to quality architecture, engineering standards, reusable frameworks, and continuous improvement programs.
Agentic understanding applied to software engineering or quality engineering.
Security Protocols
Essential
Understanding of secure software development and secure test automation practices.
Ability to protect credentials, tokens, test data, service endpoints, logs, and other sensitive information within automation and CI/CD environments.
Awareness of authentication, authorization, access control, secure API communication, and data protection requirements.
Ability to validate security-relevant behavior and ensure quality gates do not introduce avoidable security risks.
Understanding of responsible AI practices, including privacy, output verification, access control, traceability, and safe use of AI-generated code and tests.
Preferred
Exposure to security testing, vulnerability validation, threat modeling, or security-focused quality gates.
Experience integrating security scans, compliance checks, or policy controls into CI/CD pipelines.
Familiarity with secure handling of production telemetry and incident data.
Experience Requirements
Minimum 7 years of professional experience in Software Development, Software Development Engineering in Test, Quality Engineering, or a closely related engineering discipline.
Proven experience building automation frameworks from scratch and maintaining them for enterprise-scale applications.
Strong hands-on experience with Java and/or Python, Playwright, REST API testing, SQL, CI/CD quality gates, and BDD.
Experience testing microservices, distributed systems, event-driven architectures, high-availability platforms, and low-latency systems.
Demonstrated experience with performance, load, stress, resilience, regression, integration, and production validation testing.
Experience using logs, metrics, traces, and production telemetry for debugging and quality strategy.
Proven experience with AI/GenAI-assisted test design, automation development, debugging, AI output evaluation, prompt engineering, context management, SDD, Agents, Skills, and MCP integrations.
Experience owning release certification, regression strategy, incident triage, root-cause analysis, and production quality.
Experience supporting production releases and participating in on-call rotations is required.
Experience in financial services, technology, or other mission-critical environments is preferred but not required unless relevant to the assigned project.
Candidates may qualify through equivalent software engineering, automation engineering, reliability engineering, or quality architecture experience where they can demonstrate comparable technical outcomes.
Day-to-Day Activities
Design and develop automation frameworks and test solutions across UI, API, integration, event-driven, microservices, and distributed system layers.
Collaborate with developers, architects, product teams, and operations through design reviews, planning sessions, defect triage, release discussions, and incident investigations.
Execute and analyze functional, regression, performance, load, stress, resilience, and production validation tests while using telemetry to guide quality decisions.
Maintain CI/CD quality gates, evaluate AI-assisted outputs, support release certification and on-call activities, and make quality recommendations based on evidence, risk, and system behavior.
Qualifications
Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field; equivalent relevant professional experience may be considered.
Minimum 7 years of experience in software engineering, SDET, quality engineering, automation engineering, or a related discipline.
Demonstrated training or practical capability in Java/Python, Playwright, API testing, SQL, CI/CD, distributed systems, performance testing, BDD, and production quality practices.
Training or certifications in automation, cloud, Agile delivery, performance engineering, security, or AI-assisted software engineering are preferred but not required.
Commitment to continuous professional development in quality architecture, AI/GenAI, SDD, distributed systems, observability, secure engineering, and emerging testing practices.
Professional Competencies
Apply critical thinking and evidence-based problem-solving to identify quality risks, investigate failures, evaluate system behavior, and determine root causes.
Provide technical leadership by influencing testability, automation architecture, release readiness, quality standards, and engineering practices.
Communicate quality risks, test results, release recommendations, incidents, technical decisions, and improvement opportunities clearly with technical and non-technical stakeholders.
Adapt to evolving architectures, delivery models, AI/GenAI capabilities, automation tools, production requirements, and engineering priorities.
Identify and implement innovative but maintainable approaches to automation, observability, AI-assisted QE, resilience testing, quality gates, and production validation.
Manage time and priorities across framework development, test execution, defect resolution, release certification, documentation, stakeholder collaboration, and on-call responsibilities.
SYNECHRON’S DIVERSITY & INCLUSION STATEMENT
Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.
All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.
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