{"id":3315866,"url":"https://alion.io/job/virtusa-corporation-data-scientist","title":"Data Scientist","company":{"id":1833108,"name":"Virtusa Corporation","domain":"virtusa.com","url":"https://alion.io/company/virtusa-com","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":20000,"max_usd":43000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Milvus","optional":false},{"name":"MLFlow","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Search","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-26T23:23:16Z","employer_posted_date":null,"last_verified_at":"2026-10-26T23:23:16Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"Job Requirements\n\nRole Summary: \n\nWe need a skilled Senior AI Engineer to build and scale enterprise-grade Generative AI solutions. \nYou will design retrieval-augmented generation (RAG) pipelines, fine-tune large language models, and build robust data architectures, bridging the gap between heavy data engineering and advanced AI model deployment. \n\nKey Responsibilities\n\nDesign and deploy end-to-end GenAI and LLM-based applications into production.\nBuild scalable RAG architectures using vector databases and semantic search.\nOptimize data pipelines to ingest, clean, and process multi-source data for AI models.\nFine-tune, evaluate, and prompt-engineer open-source and proprietary LLMs.\nIntegrate AI services with cloud infrastructure and existing enterprise applications.\nMonitor model performance, latency, cost, and safety guardrails. \n\nRequired Skills\n\nMinimum 7 to 10 years of experience in IT Industry with 3 to 5 years in AI, LLM implementation, and Data Engineering\nGenerative AI & LLMs: RAG frameworks (LangChain, LlamaIndex), vector databases (Pinecone, Milvus, Qdrant), prompt engineering, and LLM fine-tuning.\nData Engineering: Python, SQL, ETL pipelines, Apache Spark, Kafka, and data warehousing. \nCloud & MLOps: AWS, GCP, or Azure; 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