ML Ops / Agent Ops Engineer
Location: Toronto – Hybrid at least 3 days in office
Experience: 12+ years
Please note, this role is not able to offer visa transfer or sponsorship now or in the future*
Job Description
We are seeking a highly skilled ML Ops / Agent Ops Engineer to design, build, and manage scalable AI-driven systems leveraging large language models (LLMs) and agent-based architectures. This role focuses on developing intelligent agents, implementing robust RAG pipelines, and ensuring production-grade deployment of AI solutions.
The ideal candidate will have strong expertise in Python, LLM APIs (OpenAI/Anthropic), agent orchestration frameworks, and MLOps/AgentOps practices.
Key Responsibilities
- Design and implement AI agents using frameworks such as LangGraph, CrewAI, AutoGen, or LangChain
- Build and optimize Retrieval-Augmented Generation (RAG) pipelines for knowledge retrieval and contextual reasoning
- Develop Python-based API clients for integrating LLM services
- Work with Anthropic Claude API and/or OpenAI Agents SDK, including tool use and system prompts
- Implement prompt engineering strategies, including versioning and evaluation
- Establish and manage MLOps/AgentOps pipelines for deployment and monitoring
- Integrate and manage vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma)
- Enable system monitoring through observability tools (e.g., LangSmith, Datadog, Weights & Biases)
- Ensure high performance, scalability, and reliability of AI-powered applications
Required Qualifications
- Strong proficiency in Python, including async programming and API development
- Hands-on experience with OpenAI APIs and/or Anthropic Claude API (Agent SDK preferred)
- Experience with at least one agent orchestration framework:
- LangGraph
- CrewAI
- AutoGen
- LangChain
- Experience building RAG pipelines and working with vector databases
- Familiarity with prompt engineering, versioning, and evaluation frameworks
- Understanding of MLOps or AgentOps practices, including CI/CD pipelines and monitoring
Key Skills
- Python Programming
- LLM APIs (OpenAI, Anthropic Claude)
- LangChain / LangGraph / CrewAI / AutoGen
- RAG Pipelines
- Vector Databases
- Prompt Engineering & Evaluation
- MLOps / AgentOps
- Observability & Monitoring
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Compensation: we are offering an annual salary between $69,750-$110,000
Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
At Cognizant, we're eager to meet people who believe in our mission and can make an impact in various ways! We strongly encourage you to apply even if you only meet the required skills listed. Consider what transferrable experience and skills make you an outstanding applicant and help us see how you'd be helpful to this role.
Cognizant will only consider applicants for this position who are legally authorized to work in Canada without requiring employer sponsorship, now or at any time in the future.
At Cognizant, we strive to provide flexibility wherever possible, and we are here to support a healthy work-life balance though our various wellbeing programs.
Note: The working arrangements for this role are accurate as of the date of posting. This may change based on the project you’re engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.
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关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外，候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
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