{"id":4051827,"url":"https://alion.io/job/newfold-digital-ai-software-development-engineer-in-test-ai-sdet","title":"AI - Software Development Engineer in Test (AI - SDET)","company":{"id":3068684,"name":"Newfold Digital","domain":"newfold-digital.com","url":"https://alion.io/company/newfold-digital-com","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"QA","role_family":"QA","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Context Engineering","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"GCP","optional":false},{"name":"GitHub","optional":false},{"name":"Hallucination","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Playwright","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Robot Framework","optional":false},{"name":"Scrum","optional":false},{"name":"Selenium","optional":false},{"name":"Shift-Left Security","optional":false},{"name":"SQL","optional":false},{"name":"Self-Healing","optional":true}],"status":"live","first_seen_at":"2026-11-11T01:02:49Z","employer_posted_date":null,"last_verified_at":"2026-11-11T01:02:49Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"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.Who Are We.\nNewfold Digital is a leading web technology company serving nearly seven million customers globally. Established in 2021 through the combination of leading web services providers Endurance Web Presence and Web.com Group, our portfolio of brands includes: Bluehost, BigRock, ResellerClub, CrazyDomains, HostGator, Network Solutions, Register.com, Web.com and many others.\nWe 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.\n\nKey Responsibilities\nAI/LLM Quality Engineering\nDesign, validate, and optimise testing strategies for AI-powered applications, copilots, chatbots, RAG pipelines, and autonomous AI agents.\nDevelop AI evaluation (Evals) frameworks for:Hallucination detectionGroundednessToxicity & bias validationResponse qualityContext relevancePrompt regression testingDeterminism & consistencySafety and guardrail validation\nBuild automated validation pipelines for LLM outputs using structured assertions, semantic scoring, embeddings, and evaluation metrics.\nCreate synthetic datasets and benchmark datasets for AI testing scenarios.\nTest multi-agent orchestration workflows and agent memory/context retention.\nValidate MCP (Model Context Protocol) integrations and tool interoperability.\nWork on Context Engineering, Prompt Engineering, and Prompt Optimisation strategies.\nEvaluate latency, token usage, model cost optimisation, throughput, and scalability.\nAutomation Engineering\nDevelop and maintain scalable UI/API automation frameworks using:Python (mandatory)Robot Framework (preferred)Playwright/Selenium/Cypress\nAutomate testing for:REST APIsGraphQL APIsEvent-driven systemsStreaming systemsWebhooksMicroservicesMFE (Micro Frontend) architectures\nBuild reusable automation libraries, utilities, and AI-assisted testing workflows.\nIntegrate automation into CI/CD pipelines and quality gates.\nAI Engineering & Platform Validation\nValidate RAG architectures including:Chunking strategiesEmbedding qualityRetrieval accuracyRe-rankingVector search relevance\nWork with vector databases such as:PineconeWeaviateChromaDBQdrantFAISS\nBuild or validate AI agents leveraging:LangChainLangGraphCrewAIAutoGenSemantic KernelOpenAI SDKs\nValidate AI workflows involving:Tool callingFunction callingAgent memoryAgent planning/executionMulti-modal AI systemsStructured outputs\nDevOps, Observability & Reliability\nBuild and maintain quality workflows integrated with:GitHub ActionsJenkinsGitLab CI/CDAzure DevOps\nWork with Docker and Kubernetes environments.\nPerform cloud-based testing and deployments across AWS/Azure/OCI/GCP.\nValidate distributed systems reliability and resiliency.\nMonitor AI system behaviour using observability platforms/logging/tracing tools.\nContribute to shift-left and quality engineering best practices.\n\nRequired Skills\nMust Have\nStrong programming experience in Python\nStrong understanding of Software Testing & Quality Engineering principles\nHands-on experience with:AI/LLM testingPrompt EngineeringContext EngineeringAI EvalsRAG systemsAI Agents\nExperience with:CI/CD pipelinesDocker & KubernetesCloud platforms (AWS/Azure/OCI/GCP)API testing & automationMicroservices testingUI automation\nExperience with SQL and data validation\nStrong debugging, analytical, and troubleshooting skills\nExperience working in Agile/Scrum environments\nPreferred / Good to Have\nExperience with Robot Framework\nExperience with Playwright\nKnowledge of:LangChainLangGraphLlamaIndexCrewAISemantic KernelMCP (Model Context Protocol)\nHands-on experience with:CursorGitHub CopilotClaudeGeminiOpenAI APIs\nExperience with vector databases and embeddings\nExposure to MLOps workflows and ML lifecycle testing\nKnowledge of performance testing and security testing\nExperience validating AI governance/compliance requirements\nExperience with contract testing, chaos testing, or resilience engineering\nFamiliarity with accessibility testing and cross-browser/device testing\nExposure to synthetic monitoring and production observability\nWhat We're Looking For\nEngineers who actively experiment with AI tools and build side projects, prototypes, PoCs, or open-source contributions.\nStrong problem solvers who can combine traditional QE practices with modern AI-native engineering approaches.\nPassion for innovation, developer productivity, automation acceleration, and intelligent testing.\nAbility to rapidly learn emerging AI frameworks, tools, and architectures.\nNice Portfolio Signals\nCandidates with one or more of the following will stand out:\nGitHub repositories showcasing AI/automation projects\nAI agents or copilots built personally or professionally\nContributions to open-source automation or AI ecosystems\nBlogs, talks, workshops, or technical content on AI/testing\nExperience integrating AI into SDLC or QE workflows\nExperience with autonomous testing systems or self-healing automation\nEducation\nBachelor's/Master's degree in Computer Science, Engineering, AI/ML, or related field preferred.\nEquivalent hands-on experience and demonstrable projects are highly valued.\nBonus Skills (High Impact)\nAI Red Teaming\nLLM Security Testing (Prompt Injection, Jailbreaks, Data Leakage)\nAgent Reliability & Safety Testing\nAI Cost Optimisation\nDistributed Systems Testing\nTest Data Engineering\nFeature Flag Testing\nAI Observability & Telemetry\nReinforcement Learning feedback workflows\nHuman-in-the-loop evaluation systems\nKnowledge Graph integrations\nMulti-modal AI testing (vision/audio/text)\nWhy Join Us\nWork on cutting-edge AI-native platforms and autonomous systems.\nOpportunity to shape the future of AI Quality Engineering practices, as part of the COE.\nCollaborate with high-performing engineering and AI teams.\nExposure to next-generation AI tooling, agents, and scalable cloud systems.\nCulture of innovation, experimentation, and continuous learning.\n\nWhy you'll love us.\nWe've evolved we provide three work environment scenarios. You can feel like a Newfolder in a work-from-home, hybrid, or work-from-the-office environment.\nWork-life balance. Our work is thrilling and meaningful, but we know balance is key to living well.\nWe celebrate one another's differences. We're proud of our culture of diversity and inclusion. We foster a culture of belonging. 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 have 20 + affinity groups where you can network and connect with Newfolders globally.\nWe care about you. We provide excellent benefits from OSDE 310 Health Care, Monthly Salary Reviews, Tuition Reimbursement, Internet Reimbursement, In-company English Lessons, LinkedIn learning, Referral Program Bonus, F5 extra days off, Annual Bonus, and an opportunity to work on Global projects with Multicultural team.\nWhere 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. 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