Software Development Engineer Test Engineer (Python Testing)

Experience: 9-12yrs

Location: Bangalore

CORE RESPONSIBILITIES

- Automation Architecture & Hands-On Engineering

○ Architect, scale, and maintain a modular, zero-flake E2E, API, and integration automation framework built on Python 3.10+ (pytest) and Microsoft Playwright.

○ Build resilient Playwright automation for complex stateful browser interactions, including interactive canvas and node-graph workflow editors, real-time token-streaming chat interfaces (SSE and WebSockets), multi-tab and multi-user RBAC sessions, Shadow DOM elements, and network route interception and mocking.

○ Treat test infrastructure as production software by enforcing strict static typing (mypy), fast linting (ruff), strict schema validation (Pydantic), clean design patterns (Page Object, Screenplay, and Fixture factories), and rigorous pull-request code reviews.

- Full-Stack Platform, Data & GenAI Quality

○ Validate REST, GraphQL, gRPC, and Model Context Protocol (MCP) interfaces, including optimistic concurrency and locking, idempotency, rate limiting, and asynchronous background workflows.

○ Build automated validation pipelines across heterogeneous data backends, verifying SQL query generation, semantic metric calculations, enterprise ontology graph traversals, cloud object storage ingestion, and vector similarity search retrieval.

○ Partner with AI Engineers to operationalize automated evaluation suites (RAGAS, DeepEval, LLM-as-a-Judge, and golden dataset benchmarks) measuring hallucination rates, groundedness, context recall, tool-call accuracy, Time-to-First-Token (TTFT), and token/cost regressions.

- CI/CD Release Governance, Performance & Security

○ Orchestrate containerized, parallelized (pytest-xdist and Playwright sharding) smoke, contract, and regression suites inside CI/CD pipelines with sub-15-minute PR feedback loops and automated QA to UAT to Production promotion gates.

○ Drive performance, concurrency, load, and fault-injection testing (Locust and k6) to validate high-throughput agent executions, concurrent workflow graphs, and graceful degradation during upstream LLM or database throttling.

○ Validate enterprise security boundaries including OAuth 2.0, OIDC, SAML/SSO, RBAC/ABAC permissions, multi-tenant data isolation, and OWASP Top 10 risks for both Web and LLM Applications (prompt injection, PII leakage, and excessive agency).





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- Engineering Leadership & Operational Excellence

○ Recruit, mentor, and upskill top-tier SDETs, coaching engineers from script-level testing into modern software engineering and system-level architectural thinking.

○ Partner closely with Product Management, Platform Engineering, and SRE leaders during design reviews to enforce shift-left testability and observability from day one.

○ Own platform quality SLAs and executive reporting, driving measurable improvements in Defect Escape Rate (DER), Mean Time to Detect (MTTD), Automation Stability (>99% non-flaky pass rate), and Release Lead Time.

COMPLETE TECHNOLOGY LANDSCAPE

Should bring deep hands-on mastery of our core automation stack and strong working fluency across our broader platform ecosystem:

○ Core Languages & Tooling: Python 3.10+ (asyncio, typing, uv, Poetry, ruff, mypy), TypeScript / JavaScript (ES6+, Node.js), SQL (ANSI SQL, CTEs, analytical queries), Bash / Zsh.

○ UI & Browser Automation: Microsoft Playwright (Python and TypeScript bindings, BrowserContexts, storageState authentication reuse, Trace Viewer, HAR replay, Network Interception, Canvas and Visual Regression), Chrome DevTools Protocol (CDP), Axe-core (WCAG accessibility testing).

○ Python Testing Ecosystem: pytest, pytest-xdist (parallel sharding), pytest-asyncio, Pydantic v2, httpx, aiohttp, requests, Hypothesis and Faker (property-based and synthetic test data generation).

○ API, Streaming & Contract Testing: REST (OpenAPI 3.x), GraphQL, gRPC / Protobuf, Server-Sent Events (SSE), WebSockets, Model Context Protocol (MCP), Schemathesis, Pact, WireMock.

○ AI, LLM & Agent Evaluation: DeepEval, RAGAS, LLM-as-a-Judge pipelines, Golden Dataset curation, RAG retrieval metrics (precision, recall, faithfulness, groundedness), deterministic NLP metrics (F1, Exact Match), prompt and model regression harnesses.

○ Databases, Vector & Storage Systems: PostgreSQL, Cloud Data Warehouses (BigQuery, Snowflake), Vector Databases (pgvector, Milvus, Qdrant, Pinecone),



Graph and Ontology Stores (Property Graphs, RDF), Redis, Cloud Object Storage (Google Cloud Storage, AWS S3, Azure Blob).

○ Asynchronous & Event Messaging: Kafka, RabbitMQ, Celery (testing distributed task queues, retries, dead-letter queues, and eventual consistency).

○ Performance, Load & Resilience: Locust (Python-native distributed load testing), k6, API and LLM latency profiling (p50/p95/p99, TTFT, tokens/second), fault and latency injection.

○ CI/CD, Cloud & Containers: Docker, Docker Compose, Kubernetes (K8s), GitHub Actions, GitLab CI, Jenkins, GCP / AWS / Azure.

○ Test Reporting & Observability: Allure Report, ReportPortal, TestRail / Xray, OpenTelemetry, Datadog, Grafana, Sentry, Langfuse / Arize Phoenix (LLM tracing and diagnostics).

○ Security & Identity: OAuth 2.0, OIDC, SAML / SSO, JWT, Multi-tenant RBAC / ABAC, OWASP ZAP, OWASP Top 10 for Web and LLM Applications.

MINIMUM QUALIFICATIONS

○ 9+ years of progressive experience in Software Engineering in Test (SDET) or Quality Engineering, including 3+ years directly managing, mentoring, and scaling SDET teams on complex SaaS, cloud, data, or AI platforms.

○ Expert-level proficiency designing production-grade Python (pytest) and Microsoft Playwright automation frameworks from scratch, including custom fixtures, parallel execution runners, dynamic state handling, and anti-flake architecture.

○ Strong experience testing distributed microservices, stateful workflows, real-time streaming APIs, and relational and non-relational data layers.

○ Proven track record embedding containerized automation suites into CI/CD pipelines to gate multi-workplace enterprise releases without slowing developer velocity.

○ Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or equivalent practical software engineering experience.

PREFERRED QUALIFICATIONS

- Direct experience building automated evaluation and regression pipelines for LLM Agents, RAG architectures, Semantic Layers, or Workflow Orchestration platforms.
- Hands-on experience automating visual canvas or DAG builders (such as React Flow, HTML5 Canvas, or WebGL interfaces) and MCP-based tool integrations.
- Prior experience building internal developer productivity tools, synthetic test-data platforms, or ephemeral preview test environments on Kubernetes.

📌 Software Development Engineer in Test (Python Testing) (Bengaluru)
🏢 Tredence
📍 Bengaluru