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Newfold Digital

Provides customized web presence solutions

Software Development Engineer in Test - AI

Test Automation EngineeringConfirmed live in the last 24 hours
Full-timeRemote in IndiaRemote

About the Job

Requirements

  • A Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or a related field is preferred; equivalent hands-on experience and demonstrated projects are valued.
  • Strong programming experience in Python.
  • Strong understanding of software testing and quality engineering principles.
  • Hands-on experience with AI/LLM testing, prompt engineering, context engineering, AI evaluations, RAG systems, and AI agents.
  • Experience with CI/CD pipelines, Docker and Kubernetes, cloud platforms (AWS, Azure, OCI, or GCP), API testing and automation, microservices testing, and UI automation.
  • Experience with SQL and data validation.
  • Experience working in Agile/Scrum environments.
  • Experience with Robot Framework is preferred.
  • Experience with Playwright is preferred.
  • Knowledge of LangChain, LangGraph, LlamaIndex, CrewAI, Semantic Kernel, and MCP (Model Context Protocol) is preferred.
  • Hands-on experience with Cursor, GitHub Copilot, Claude, Gemini, and OpenAI APIs is preferred.
  • Experience with vector databases and embeddings is preferred.
  • Exposure to MLOps workflows and ML lifecycle testing is preferred.
  • Knowledge of performance testing and security testing is preferred.
  • Experience validating AI governance and compliance requirements is preferred.
  • Experience with contract testing, chaos testing, or resilience engineering is preferred.
  • Familiarity with accessibility testing and cross-browser/device testing is preferred.
  • Exposure to synthetic monitoring and production observability is preferred.
  • AI red teaming, LLM security testing (prompt injection, jailbreaks, and data leakage), agent reliability and safety testing, AI cost optimization, distributed systems testing, test data engineering, feature flag testing, AI observability and telemetry, reinforcement-learning feedback workflows, human-in-the-loop evaluation systems, knowledge graph integrations, and multimodal AI testing are bonus skills.
  • Experience with GitHub repositories showcasing AI/automation projects, personally or professionally built AI agents or copilots, open-source automation or AI ecosystem contributions, AI/testing blogs, talks, workshops or technical content, integrating AI into SDLC or QE workflows, or autonomous testing systems or self-healing automation are portfolio signals that will stand out.
  • The posting values experimentation with AI tools and side projects, prototypes, proofs of concept, or open-source contributions.
  • The role calls for combining traditional quality engineering practices with modern AI-native engineering approaches and the ability to learn emerging AI frameworks, tools, and architectures.

Responsibilities

  • Design, validate, and optimize testing strategies for AI-powered applications, copilots, chatbots, RAG pipelines, and autonomous AI agents.
  • Develop AI evaluation frameworks for hallucination detection, groundedness, toxicity and bias validation, response quality, context relevance, prompt regression testing, determinism and consistency, and safety and guardrail validation.
  • Build automated validation pipelines for LLM outputs using structured assertions, semantic scoring, embeddings, and evaluation metrics.
  • Create synthetic datasets and benchmark datasets for AI testing scenarios.
  • Test multi-agent orchestration workflows and agent memory/context retention.
  • Validate MCP (Model Context Protocol) integrations and tool interoperability.
  • Work on context engineering, prompt engineering, and prompt optimization strategies.
  • Evaluate latency, token usage, model cost optimization, throughput, and scalability.
  • Develop and maintain scalable UI/API automation frameworks using Python and, where applicable, Robot Framework, Playwright, Selenium, or Cypress.
  • Automate testing for REST APIs, GraphQL APIs, event-driven systems, streaming systems, webhooks, microservices, and micro-frontend architectures.
  • Build reusable automation libraries, utilities, and AI-assisted testing workflows.
  • Integrate automation into CI/CD pipelines and quality gates.
  • Validate RAG architectures, including chunking strategies, embedding quality, retrieval accuracy, re-ranking, and vector search relevance.
  • Work with vector databases such as Pinecone, Weaviate, ChromaDB, Qdrant, and FAISS.
  • Build or validate AI agents leveraging LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, and OpenAI SDKs.
  • Validate AI workflows involving tool calling, function calling, agent memory, agent planning and execution, multimodal AI systems, and structured outputs.
  • Build and maintain quality workflows integrated with GitHub Actions, Jenkins, GitLab CI/CD, and Azure DevOps.
  • Work with Docker and Kubernetes environments.
  • Perform cloud-based testing and deployments across AWS, Azure, OCI, and GCP.
  • Validate distributed systems reliability and resiliency.
  • Monitor AI system behaviors using observability platforms and logging/tracing tools.
  • Contribute to shift-left and quality engineering best practices.

Desired Qualifications

  • Experience with Robot Framework.
  • Experience with Playwright.
  • Knowledge of LangChain, LangGraph, LlamaIndex, CrewAI, Semantic Kernel, and MCP (Model Context Protocol).
  • Hands-on experience with Cursor, GitHub Copilot, Claude, Gemini, and OpenAI APIs.
  • Experience with vector databases and embeddings.
  • Exposure to MLOps workflows and ML lifecycle testing.
  • Knowledge of performance testing and security testing.
  • Experience validating AI governance and compliance requirements.
  • Experience with contract testing, chaos testing, or resilience engineering.
  • Familiarity with accessibility testing and cross-browser/device testing.
  • Exposure to synthetic monitoring and production observability.
  • Bonus skills include AI red teaming; LLM security testing (prompt injection, jailbreaks, and data leakage); agent reliability and safety testing; AI cost optimization; distributed systems testing; test data engineering; feature flag testing; AI observability and telemetry; reinforcement-learning feedback workflows; human-in-the-loop evaluation systems; knowledge graph integrations; and multimodal AI testing (vision, audio, and text).
  • Portfolio signals that will stand out include GitHub repositories showcasing AI/automation projects; AI agents or copilots built personally or professionally; contributions to open-source automation or AI ecosystems; blogs, talks, workshops, or technical content on AI/testing; experience integrating AI into SDLC or QE workflows; and experience with autonomous testing systems or self-healing automation.

About the Company

Newfold Digital

Provides customized web presence solutions

Newfold Digital helps small- and medium-sized businesses build and manage their online presence by offering a broad portfolio of web presence tools and personalized support. Customers pick hosting, domains, content management, security, email, and related services, then combine them into a customized package with setup help and ongoing guidance. It stands out by pairing a wide product suite with tailored support and customization, instead of one-size-fits-all solutions. Its goal is to deliver measurable value for customers by helping them create a successful online presence through practical, customized products and hands-on help.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Jacksonville, FL
Founded
2021

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