Software Development Engineer in Test - AI

This role goes beyond traditional QA; the ideal candidate should be capable of validating, evaluating, and improving AI-powered systems, agents, copilots, and LLM-driven workflows while building scalable automation frameworks and intelligent quality solutions. You will work closely with Engineering, AI/ML, Platform, Product, and DevOps teams to ensure reliability, safety, observability, scalability, and quality of modern AI-native applications and Agentic systems. What you'll do & how you'll make your mark.

AI/LLM Quality Engineering Design, validate, and optimize testing strategies for AI-powered applications, copilots, chatbots, RAG pipelines, and autonomous AI agents.

About Web

• Who we are.
• Newfold Digital is a leading web technology company serving millions of customers globally.
• Our customers know us through our robust portfolio of brands.
• We have some of the industry's most prominent and storied go-to-market brands, including Bluehost, HostGator, Domain.com, Network Solutions, Register.com and Web.com.
• We help customers of all sizes build a digital presence that delivers results.
• With our extensive product offerings and personalized support, we take pride in collaborating with our customers to serve their online presence needs.
• The strength of our company lives in the intersection of our people, our customers, and our brands.
• We celebrate one another’s differences.
• We’re proud of our culture of diversity and inclusion.
• We foster a culture of belonging.
• We have 20 + affinity groups where you can network and connect with Newfolders globally.
• We care about you.
• We are a family, and we care about you and your family’s physical and mental health by providing competitive HMO benefits – 175k MBL with one free dependent upon one year of service!
• Unfold new possibilities with #teamnewfold!

Responsibilities

• 1.
• Hallucination detection
• Groundedness Toxicity & bias validation
• Response quality Context relevance Prompt regression testing
• Determinism & consistency

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.
• 2.
• Engineering Develop and maintain scalable UI/API automation frameworks using: Python (mandatory)Robot Framework (preferred)Playwright/Selenium/Cypress.
• REST APIs GraphQL APIs Event-driven systems Streaming systems Webhooks Microservices MFE (Micro Frontend) architectures.
• Build reusable automation libraries, utilities, and AI-assisted testing workflows.
• Integrate automation into CI/CD pipelines and quality gates.
• 3.
• AI Engineering & Platform Validation Validate RAG architectures including
• Chunking strategies Embedding quality
• Retrieval accuracy Re-ranking Vector search relevance
• Pinecone Weaviate ChromaDB Qdrant FAISS Build or validate AI agents leveraging: LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel OpenAI SDKs Validate AI workflows involving: Tool calling

Function calling Agent memory

• DevOps, Observability & Reliability Build and maintain quality workflows integrated with: GitHub Actions Jenkins GitLab CI/CD Azure DevOps Work with Docker and Kubernetes environments.
• Perform cloud-based testing and deployments across AWS/Azure/OCI/GCP.
• Validate distributed systems reliability and resiliency.
• AI system behaviors using observability platforms/logging/tracing tools.
• Contribute to shift-left and quality engineering best practices.
• Who you are & what you'll need to succeed.

Requirements

Agent planning/execution Multi-modal AI systems

• Structured outputs 4.
• Bachelor’s/Master’s degree in Computer Science, Engineering, AI/ML, or related field preferred.
• Strong programming experience in Python Strong understanding of Software Testing & Quality Engineering principles Hands-on experience with: AI/LLM testing Prompt Engineering Context Engineering AI Evals RAG systems AI Agents Experience with: CI/CD pipelines Docker & KubernetesCloud platforms (AWS/Azure/OCI/GCP) API testing & automation
• Microservices testing UI automation
• Experience with SQL and data validation
• Strong debugging, analytical, and troubleshooting skills
• Experience working in Agile/Scrum environments

Preferred

• Equivalent hands-on experience and demonstrated projects are highly valued.
• Experience with Robot Framework Experience with Playwright Knowledge of: LangChain, LangGraph, LlamaIndex CrewAI Semantic Kernel MCP (Model Context Protocol) Hands-on experience with: Cursor GitHub Copilot Claude Gemini 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/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

• Skills (High Impact) AI Red Teaming LLM Security Testing (Prompt Injection, Jailbreaks, Data Leakage) Agent Reliability & Safety Testing AI Cost Optimization Distributed Systems Testing Test Data Engineering Feature Flag Testing AI Observability & Telemetry Reinforcement Learning feedback workflows Human-in-the-loop evaluation systems
• Knowledge Graph integrations Multi-modal AI testing (vision/audio/text) What We’re Looking For Engineers who actively experiment with AI tools and build side projects, prototypes, PoCs, or open-source contributions.
• Strong problem solvers who can combine traditional QE practices with modern AI-native engineering approaches.
• Passion for innovation, developer productivity, automation acceleration, and intelligent testing.
• Ability to rapidly learn emerging AI frameworks, tools, and architectures.
• Portfolio Signals Candidates with one or more of the following will stand out: 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
• Experience with autonomous testing systems or self-healing automation

Benefits

• Why you'll love us.
• Work-life balance.
• Our work is thrilling and meaningful, but we know balance is key to living well.
• Our company and customers benefit when employees bring their authentic selves to work.
• We have programs that bring us together on important issues and provide learning and development opportunities for all employees.
• We also give out Punctuality Bonus, Generous Vacation policy, and much more!
• Where can we take you?
• We’re fans of helping our employees learn different aspects of the business, be challenged with new tasks, be mentored, and grow their careers.

This

Job Description includes the essential job functions required to perform the job described above, as well as additional duties and responsibilities.

This

Job Description is not an exhaustive list of all functions that the employee performing this job may be required to perform. The Company reserves the right to revise the Job Description at any time, and to require the employee to perform functions in addition to those listed above.