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Bidgely

Energy data analytics with disaggregation insights

Software Development Engineer in Test 3

Test Automation EngineeringConfirmed live in the last 24 hours
Full-timeRemote in IndiaNo salary listedRemote

About the Job

Requirements

  • Six to nine years of software testing experience, including hands-on SDET experience.
  • Good working knowledge of Python and Java.
  • Experience owning test strategy and improving automation and release quality.
  • Experience with UI automation using Selenium or Playwright.
  • Experience building API automation and end-to-end frameworks with CI/CD.
  • Ability to analyse product requirements and identify testing gaps.
  • Prior experience testing chatbots, IVRs, and GenAI agents.
  • Experience designing evaluations, rubrics, and LLM-as-judge evaluations.
  • Working knowledge of LangChain, LangGraph, and LangSmith or similar tools.
  • Experience building evaluation harnesses or tooling for AI agents.
  • Strong analytical and communication skills.

Responsibilities

  • Own test strategy and release quality criteria for the product area.
  • Build and maintain UI automation using Selenium or Playwright, API automation, and end-to-end regression suites.
  • Design evaluation strategy for AI agents using LLM-as-judge, rubrics, and other evaluation techniques.
  • Build evaluation datasets and automated evaluation suites in Python, integrated with CI/CD.
  • Test AI agents for accuracy, consistency, tool usage, safety, and data handling.
  • Debug agent failures using LangSmith and similar AI observability tools.
  • Analyse release-over-release quality and identify regressions.
  • Review product requirements and identify gaps in requirements and test coverage.
  • Review test code, set testing standards, and mentor SDETs.
  • Communicate findings and recommendations to engineering, product, and leadership.

About the Company

Bidgely

Energy data analytics with disaggregation insights

Bidgely provides energy analytics that break down a building’s total energy use into appliance-level usage for utilities, SMBs, and consumers. It collects energy data and uses AI to identify how much power each appliance consumes, with tools like Home Energy Reports, Enterprise Analytics, and EV Analytics, plus services such as virtual energy assessments and smart alerts. Its edge comes from appliance-level disaggregation paired with a full analytics suite and services that cover gas, electrification, and decarbonization, enabling personalized insights and scalable demand management beyond basic usage data. The goal is to help utilities and end users save energy and reduce costs while advancing decarbonization and electrification of the energy system.

Company size
201-500
Company stage
Late Stage VC
Total funding
$110.6M
Headquarters
Mountain View, CA
Founded
2011

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