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SDET With Python Full Stack developer_Dallas,TX_F2F interview

KeylentDallas, TX🇺🇸United StatesPosted 19 Aug 2026

Quick Overview

Work Type
On Site
Level
Mid Senior

Job Description

Senior SDET / QA Automation Engineer (Agentic AI & Full-Stack) 

Dallas, TX – In-person interview is mandatory

Need strong Python and AWS Bedrock experience

Summary

We’re looking for a Senior SDET with strong full‑stack engineering skills, deep experience in backend and service‑level development, and the ability to build scalable test application in Python or Java. This role blends frontend and backend development, cloud‑native testing, and AI-augmented quality engineering with a heavy focus on building and deploying autonomous, multi-agent frameworks, tool-calling mechanisms, and complex agentic workflows using Amazon Bedrock and modern LLMs.

Key Responsibilities

  • Build and maintain automation frameworks for API, microservices, frontend UI, and integration testing.
  • Develop internal tools, SDKs, and test harnesses that improve developer productivity and system reliability.
  • Contribute to frontend development using modern frameworks such as React, Angular, or Vue, ensuring testability and accessibility.
  • Contribute to backend development of microservices, APIs, and distributed systems using Python or Java.
  • Architect CI/CD‑ready test pipelines integrated with AWS cloud infrastructure (Lambda, ECS/EKS, S3, CloudWatch, DynamoDB).
  • Implement AI‑augmented testing workflows using Amazon Bedrock for automated test generation, log analysis, and anomaly detection.
  • Build performance, load, and resilience testing strategies for both frontend and backend systems.
  • Collaborate with engineering teams to design testable architectures, enforce quality gates, and improve observability.
  • Drive root‑cause analysis for production issues and build automated regression protections.
  • Mentor engineers on automation, code quality, and AI‑assisted testing best practices.
  • Architect, build, and maintain autonomous multi-agent testing workflows, enabling agents to self-heal test code, discover edge cases, and reason through end-to-end user journeys independently.
  • Implement advanced AI patterns including multi-agent orchestration, vector embeddings for test-state memory, tool calling, and human-in-the-loop validation mechanisms.
  • Establish strict evaluation and guardrail frameworks to measure agent accuracy, hallucinations, and performance degradation in production-grade testing tools.

 

Required Qualifications

  • 10+ years as an SDET, Software Engineer, or Full‑Stack Developer.
  • Strong coding skills in Python or Java with production‑grade engineering experience.
  • Hands‑on frontend development experience (React, Angular, Vue, or similar).
  • Hands‑on backend development experience with APIs, microservices, and distributed systems.
  • Expertise in API testing, contract testing, and service‑level automation.
  • Experience building automation frameworks from scratch.
  • Strong understanding of CI/CD pipelines and automated quality gates.
  • Experience with AWS services (EC2, Lambda, S3, IAM, CloudFormation/Terraform).
  • Experience integrating or building solutions using LLMs or Amazon Bedrock.
  • Agentic AI Experience: Hands-on experience building and deploying production-ready agentic applications or multi-agent workflows.
  • AI Orchestration Frameworks: Deep familiarity with agentic frameworks such as LangChain, CrewAI, AutoGen, or LlamaIndex.
  • Advanced AI Patterns: Solid understanding of LLM reasoning patterns, retrieval-augmented generation (RAG), function calling/tool execution, and agent memory management.
  • Familiarity with containers (Docker) and orchestration (Kubernetes).

Preferred Qualifications

  • Experience with frontend automation tools (Playwright, WebdriverIO).
  • Experience with distributed tracing and observability tools (CloudWatch, Datadog, OpenTelemetry).
  • Knowledge of performance testing tools (k6, Gatling, Locust).
  • Experience with event‑driven architectures (Kafka, SNS/SQS).
  • Background in security testing or chaos engineering.
  • Contributions to internal or open‑source testing frameworks.

Soft Skills

  • Strong communication and ability to influence engineering teams.
  • Passion for automation, developer experience, and AI‑driven quality engineering.
  • Ability to lead initiatives and drive quality strategy across teams.

Skills

Docker
DynamoDB
Microservices
AWS
Angular
CloudFormation
Datadog
Gatling
Java
Kafka
Kubernetes
LLM
Playwright
Python
React
Terraform
Vue
k6

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