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AgentOps

Virtusa

Role overview

Qualifications

  • 5+ years of experience in Software Engineering, Machine Learning Engineering, or AI Engineering.
  • Strong proficiency in Python and modern software engineering best practices.
  • Hands-on experience building and deploying production-grade GenAI, Agentic AI, or LLM-powered applications.
  • Experience with AgentOps platforms such as LangSmith, Langfuse, Databricks, MLflow, or similar observability and evaluation tools.

Responsibilities

  • Adopt AgentOps framework into production-grade GenAI and Agentic AI solutions.
  • Refactor production-grade code and provide API provision.
  • Utilize strong debugging, troubleshooting, and performance optimization skills.
  • Collaborate effectively across cross-functional teams.

Key facts

  • Remote from: Anywhere
  • Full time
  • Senior (5-10 years)
  • English

Hard skills

Other skills

  • Troubleshooting (Problem Solving)
  • Governance
  • Communication
  • Collaboration

About the company

Virtusa logo

Virtusa

Virtusa Corporation is a global provider of Digital Business Transformation, Digital Engineering, and Information Technology (IT) outsourcing services that accelerate our clients’ journey to their Digital Future. Virtusa serves Global 2000 companies in Banking, Financial Services, Insurance, Healthcare, Telecommunications, Media, Entertainment, Travel, Manufacturing, and Technology industries. Using a combination of digital strategy, digital engineering, business implementation, and IT platform modernization services, Virtusa helps clients execute successful end-to-end digital business transformation initiatives. Virtusa engages its clients to re-imagine their business models and develop strategies to defend and grow their business by introducing innovative products and services, developing distinctive digital consumer experiences, creating operational efficiency using digital labor, developing operational and IT platforms for the future, and rationalizing and modernizing their existing IT applications infrastructure. As a result, its clients are simultaneously able to drive business growth through digital-first customer experiences, while also consolidating and modernizing their IT application infrastructure to support digital business transformation. Holding a proven record of success across industries, Virtusa readily understands its clients' business challenges and uses its domain expertise to deliver innovative applications of technology to address its clients’ critical business challenges. Examples include building the world's largest property & casualty claims modernization program; one of the largest corporate customer portals for a premier global bank; an order to cash implementation for a multinational telecommunications provider; and digital transformation initiatives for media and banking companies. Founded in 1996 and headquartered in Massachusetts, Virtusa has operations in North America, Europe, and Asia.

Company details

Company size10001

Links

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Job description

This is a remote position.

We are seeking an experienced AgentOps(Machine Learning Engineer) to adopt AgentOps framework into production-grade GenAI and Agentic AI solutions. The ideal candidate has strong Python engineering skills(API provision, production-grade code refactoring), hands-on experience with AgentOps frameworks(LangSmith/LangFuse/Phoenix etc).

Requirements

• 5+ years of experience in Software Engineering, Machine Learning Engineering, or AI Engineering.
• Strong proficiency in Python and modern software engineering best practices.
• Hands-on experience building and deploying production-grade GenAI, Agentic AI, or LLM-powered applications.
• Experience with AgentOps platforms such as LangSmith, Langfuse, Databricks, MLflow, or similar observability and evaluation tools.
• Strong understanding of RAG, prompt engineering, tool calling, agent memory, and multi-agent architectures.
• Experience with agent orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or similar technologies.
• Strong debugging, troubleshooting, and performance optimization skills.
• Excellent communication and collaboration skills, with the ability to work effectively across cross-functional teams.
Preferred Qualifications
• Experience with MLOps, LLMOps, or AgentOpspractices in enterprise environments.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and container technologies (Docker, Kubernetes).
• Experience implementing AI evaluation, monitoring, and governance frameworks.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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