Salary
≈ $20k – $43k per year (Estimated)
Location
In office (Bengaluru)
Experience
7+ years exp
Employment
Full-Time
First seen by Alion on Oct 26, 2026.
Overview
Company
Impact
Profile match
Virtusa (Virtusa Corporation) is a global digital engineering and information technology services company that provides digital transformation, IT consulting, cloud modernization, and systems integration solutions. Headquartered in Southborough, Massachusetts, the firm operates delivery centers and regional hubs across North America, Europe, and the Asia-Pacific region - with major operational bases in India and Sri Lanka. Founded in 1996, it serves Global 2000 enterprises across sectors such as banking and financial services, healthcare, life sciences, telecommunications, insurance, and retail, utilizing an engineering-led approach to optimize core platforms, deploy AI-driven capabilities, and accelerate business operations.
Backed by CRV
Job Requirements
Role Summary:
7-10Years
Role Summary:
- We need a skilled Senior AI Engineer to build and scale enterprise-grade Generative AI solutions.
- You 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.
- Design and deploy end-to-end GenAI and LLM-based applications into production.
- Build scalable RAG architectures using vector databases and semantic search.
- Optimize data pipelines to ingest, clean, and process multi-source data for AI models.
- Fine-tune, evaluate, and prompt-engineer open-source and proprietary LLMs.
- Integrate AI services with cloud infrastructure and existing enterprise applications.
- Monitor model performance, latency, cost, and safety guardrails.
- Minimum 7 to 10 years of experience in IT Industry with 3 to 5 years in AI, LLM implementation, and Data Engineering
- Generative AI & LLMs: RAG frameworks (LangChain, LlamaIndex), vector databases (Pinecone, Milvus, Qdrant), prompt engineering, and LLM fine-tuning.
- Data Engineering: Python, SQL, ETL pipelines, Apache Spark, Kafka, and data warehousing.
- Cloud & MLOps: AWS, GCP, or Azure; Docker, Kubernetes, and MLflow/Kubeflow.
- Software Engineering: Clean code practices, REST APIs, and microservices architecture
7-10Years
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