{"id":2180868,"url":"https://alion.io/job/hcltech-sdet-senior-test-lead-4","title":"SDET Senior Test Lead","company":{"id":225,"name":"HCLTech","domain":"hcltech.com","url":"https://alion.io/company/hcltech","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"QA","role_family":"QA","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":14500,"max_usd":41000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":9},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Confluence","optional":false},{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Hallucination","optional":false},{"name":"Hybrid Search","optional":false},{"name":"Jira","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"Postman","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Rest API","optional":false},{"name":"Rest-Assured","optional":false},{"name":"Robot Framework","optional":false},{"name":"Scrum","optional":false},{"name":"DeepEval","optional":true},{"name":"k6","optional":true},{"name":"Locust","optional":true},{"name":"pySpark","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-09T14:58:07Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-22T10:45:43Z","board_verified":true,"closed_at":null,"days_open":12,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":12},"description":"Job Summary\nWe are looking for an experienced QA Engineer with a strong background in both functional and automated testing, and a working understanding of AI and machine learning concepts. This role is central to ensuring the quality, reliability, and trustworthiness of enterprise-grade AI solutions - spanning traditional ML models, Generative AI applications, RAG pipelines, agentic workflows, and the data pipelines that power them.\nThis is not a generic QA role. The ideal candidate understands how AI systems behave differently from traditional software - where outputs are probabilistic rather than deterministic, where correctness is contextual, and where testing strategies must account for model drift, hallucination, retrieval quality, and data integrity. You will work alongside AI Engineers, data engineers, and architects to define test strategies, build validation frameworks, and deliver clear, actionable quality reports to technical and non-technical stakeholders.\nKey Responsibilities\nFunctional Testing\nDesign, execute, and maintain comprehensive test plans and test cases for AI/ML solutions, Generative AI applications, RAG pipelines, agentic workflows, and supporting REST APIs.\nValidate end-to-end functional behaviour of AI and its integrated solutions against defined acceptance criteria and business requirements.\nTest ML model outputs for correctness, consistency, and alignment with expected behaviour - including classification results, predictions, anomaly flags, and recommendations.\nEvaluate RAG pipeline quality: validate retrieval relevance, chunking effectiveness, reranking behaviour, hybrid search results, and the accuracy of LLM-generated responses against source documents.\nTest agentic AI workflows for correct tool/function invocation, reasoning logic, multi-step task completion, and appropriate handling of edge cases and failures.\nConduct API testing to validate request/response behaviour, error handling, authentication, input validation, and performance under load. Official Use Only\nPerform data pipeline testing: validate data ingestion, transformation, cleansing, and output quality across batch and streaming workflows.\nExecute regression testing following model updates, pipeline changes, or infrastructure modifications.\nTest non-functional requirements including latency, throughput, scalability, and resilience.\nConduct exploratory testing to surface unexpected or emergent behaviours in AI systems - particularly in agentic and LLM-based solutions. Test Automation\nDesign and implement automated test frameworks and suites for AI solutions, APIs, and data pipelines.\nBuild reusable, maintainable automation scripts in Python, integrating with testing frameworks such as pytest, Robot Framework, or equivalent.\nDevelop automated regression suites that can be integrated into CI/CD pipelines to enable continuous quality validation.\nImplement automated evaluation pipelines for Generative AI outputs - including LLM-as-judge scoring, semantic similarity checks, factual grounding validation, and response consistency testing.\nAutomate data quality checks within Databricks or equivalent pipeline environments to validate schema, completeness, referential integrity, and statistical distributions.\nIntegrate test automation with monitoring and alerting tools to detect quality degradation in deployed AI solutions. AI-Specific Validation\nEvaluate LLM outputs for hallucination, factual accuracy, relevance, coherence, and adherence to safety and content guidelines.\nValidate embedding quality, vector search precision/recall, and metadata filtering behaviour in RAG architectures.\nTest model fairness, consistency, and robustness across diverse inputs, including adversarial and edge-case scenarios.\nValidate that responsible AI principles - including content safety filters, guardrails, and bias mitigations - are functioning as designed. Official Use Only\nSupport model drift monitoring by defining baseline benchmarks and alerting thresholds for deployed ML models. Reporting & Stakeholder Communication\nProduce clear, well-structured test reports summarizing test coverage, results, defect trends, quality risks, and recommendations - tailored for both technical and non-technical audiences.\nMaintain dashboards and metrics that provide ongoing visibility into solution quality, test execution progress, and open defects.\nDocument defects clearly, with reproducible steps, expected vs. actual behavior, severity assessment, and supporting evidence (logs, screenshots, sample data).\nSkill Requirements\nFunctional Testing\nProven experience in functional, integration, regression, and exploratory testing of complex software systems.\nStrong ability to analyse requirements, design test strategies, and write high-quality test cases with clear pass/fail criteria.\nExperience testing REST APIs using tools such as Postman, REST Assured, or equivalent.\nFamiliarity with testing data-intensive applications, including validation of pipeline outputs and structured/unstructured data quality.\nExperience working in Agile/Scrum delivery environments, including sprint-based test planning and execution.\nTest Automation\nHands-on experience building and maintaining automated test suites using Python-based frameworks (pytest preferred).\nOfficial Use Only\nExperience integrating test automation into CI/CD pipelines (GitHub Actions, Azure DevOps, or equivalent).\nAbility to write clean, maintainable automation code following good software engineering practices.\nExperience with API test automation and data validation automation.\nAI & Domain Knowledge\nWorking knowledge of AI and ML concepts: understanding of how models are trained, evaluated, and deployed - and the implications for testing strategies.\nFamiliarity with Generative AI concepts: LLMs, RAG pipelines, embeddings, vector search, chunking, reranking, and agentic workflows.\nAbility to evaluate LLM output quality, including identifying hallucinations, factual errors, relevance gaps, and unsafe content.\nUnderstanding of AI non-determinism and how to design testing approaches that account for probabilistic outputs (e.g., semantic equivalence checks rather than exact string matching).\nAwareness of responsible AI principles: content safety, bias, fairness, and transparency.\nReporting & Communication\nStrong written communication skills, with the ability to produce clear, professional test reports and defect documentation.\nAbility to distil technical quality findings into concise summaries suitable for non-technical stakeholders.\nExperience maintaining test metrics and quality dashboards - using tools such as Azure DevOps, Jira, Confluence, or equivalent.\nComfortable presenting quality status and risks in team meetings and sprint ceremonies.\nTools & Platform Familiarity\nFamiliarity with Azure cloud services relevant to AI solutions: Azure OpenAI, Azure AI Search, Azure Databricks, and ADLS - sufficient to understand system architecture and design targeted test scenarios.\nExperience with version control (Git) and collaborative development workflows.\nFamiliarity with logging and observability tools (e.g., Azure Application Insights) to support defect investigation and root cause analysis.\nOther Requirements\nNice to Have\nHands-on experience with LLM evaluation frameworks such as RAGAS, DeepEval, or LLM-as-judge implementations.\nExperience with performance/load testing tools (e.g., Locust, k6, or Azure Load Testing).\nExposure to Databricks notebooks or PySpark for data pipeline validation.\nExperience testing ML model fairness and bias using tools such as Fairlearn or equivalent.\nISTQB certification or equivalent formal QA qualification.\nExperience in a data engineering or AI engineering adjacent role - providing deeper empathy for the systems being tested.","description_format":"text","description_chars":7795,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","IT Outsourcing & Dedicated Teams","Systems Integrators"],"lifecycle":[{"event":"open","at":"2026-10-09T14:58:07Z"}],"visa":[],"liveness":{"score":84,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.936,"p_room":0.9,"age_days":12,"expected_fill_days":23,"reasons":["conf:3","wave","velocity","win:mid","comp:brand"],"computed_at":"2026-10-22T06:10:10Z"},"pay":null,"html_url":"https://alion.io/job/hcltech-sdet-senior-test-lead-4","json_url":"https://alion.io/job/hcltech-sdet-senior-test-lead-4.json","meta":{"generated_at":"2026-10-22T11:25:56Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":9346,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-23T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":225},"rest":"https://alion.io/mcp/rest/get_company?id=225"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fhcltech-sdet-senior-test-lead-4"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fhcltech-sdet-senior-test-lead-4"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fhcltech-sdet-senior-test-lead-4"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/hcltech-sdet-senior-test-lead-4\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fhcltech-sdet-senior-test-lead-4"}]}