Usage of Conventional AI
Virtusa utilizes Artificial Intelligence (AI) technology for the purpose of conducting candidate pre-employment assessments. This AI may include both text-based and voice-based functionalities. The AI technology will have access to the data that you upload or provide during your interaction with the AI bot and will use such data solely for the purpose of performing assessment in accordance with Virtusa policies and practices. The AI is not used to substantially assist or replace discretionary employment decisions. Read our full employee privacy policy here.
Job description
We are looking for 12 experienced highly skilled Lead Engineer/Senior Lead Engineer with Experience in designing and optimizing data pipelines for Generative AI solutions, integrating LLMs with RAG frameworks using Python, vector databases, and orchestration tools like LangChain/LangGraph. Well versed with AI Agent Development & Frameworks: Design and scale multi-agent systems using LangGraph/Google ADK to automate complex Root Cause Analysis (RCA) and operational data engineering challenges. Build Human-in-the-Loop agentic workflows that provide actionable recommendations with manual approval gates for critical actions. Develop AI-driven diagnostic tools to correlate job failures and SLA breaches across AWS and Databricks. Collaborate with cross-functional teams (product, Engineering and research) to define and deliver AI-powered solutions. Evaluate and select appropriate generative AI architectures and frameworks. Finetune and optimize LLMs for specific use cases and domains.Establish LLM observability to monitor agent performance, detect hallucinations, and implement iterative updates to prompt chains. Implement AI guardrails and security protocols to prevent prompt injection and ensure the protection of sensitive data.Document and maintain AI agent architectures, data pipeline integrations, and deployment lifecycles. Hands on exposure in LangChain / LangGraph Frameworks for orchestration. RAG (Retrieval-Augmented Generation) implementation Expert level Python with asynchronous programming and data processing libraries (PySpark, Pandas). Advanced proficiency in LangGraph/LangChain or Google ADK for building stateful, multi-agent applications.Deep understanding of transformer models, attention mechanisms, and fine-tuning techniques. Hands-on experience with vector databases and advanced retrieval strategies. LLM Observability, familiarity with agentic AI evaluation and monitoring tools. Hands-on experience with the AWS ecosystem for AI.Hands-on experience with Databricks, Delta Lake and Mosaic AI.Familiarity with developing and managing workflows using Airflow DAGs. Knowledge of LLM Fine-Tuning (LoRA, PEFT). Containerization & Orchestration (Docker, Kubernetes). Monitoring & Observability (MLflow, Prometheus for AI systems)
Qualification
We are looking for 12 experienced highly skilled Lead Engineer/Senior Lead Engineer with Experience in designing and optimizing data pipelines for Generative AI solutions, integrating LLMs with RAG frameworks using Python, vector databases, and orchestration tools like LangChain/LangGraph. Well versed with AI Agent Development & Frameworks: Design and scale multi-agent systems using LangGraph/Google ADK to automate complex Root Cause Analysis (RCA) and operational data engineering challenges. Build Human-in-the-Loop agentic workflows that provide actionable recommendations with manual approval gates for critical actions. Develop AI-driven diagnostic tools to correlate job failures and SLA breaches across AWS and Databricks. Collaborate with cross-functional teams (product, Engineering and research) to define and deliver AI-powered solutions. Evaluate and select appropriate generative AI architectures and frameworks. Finetune and optimize LLMs for specific use cases and domains.Establish LLM observability to monitor agent performance, detect hallucinations, and implement iterative updates to prompt chains. Implement AI guardrails and security protocols to prevent prompt injection and ensure the protection of sensitive data.Document and maintain AI agent architectures, data pipeline integrations, and deployment lifecycles. Hands on exposure in LangChain / LangGraph Frameworks for orchestration. RAG (Retrieval-Augmented Generation) implementation Expert level Python with asynchronous programming and data processing libraries (PySpark, Pandas). Advanced proficiency in LangGraph/LangChain or Google ADK for building stateful, multi-agent applications.Deep understanding of transformer models, attention mechanisms, and fine-tuning techniques. Hands-on experience with vector databases and advanced retrieval strategies. LLM Observability, familiarity with agentic AI evaluation and monitoring tools. Hands-on experience with the AWS ecosystem for AI.Hands-on experience with Databricks, Delta Lake and Mosaic AI.Familiarity with developing and managing workflows using Airflow DAGs. Knowledge of LLM Fine-Tuning (LoRA, PEFT). Containerization & Orchestration (Docker, Kubernetes). Monitoring & Observability (MLflow, Prometheus for AI systems)
Key job details
About Virtusa
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 30,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.
Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.
Virtusa is an Equal Opportunity Employer. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government-issued ID during each interview. All candidates must be authorized to work in the USA.
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