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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私たちについて：
コグニザント（NASDAQ: CTSH）は、AI builderおよびテクノロジーサービスプロバイダとして、AI投資を企業価値へとつなげるフルスタックのAIソリューションを提供しています。業界、業務プロセス、エンジニアリングに関する深い専門性を強みに、各企業固有のコンテキストをテクノロジーシステムに組み込み、人の力を最大限に引き出すとともに、具体的な成果の創出と、急速に変化する世界におけるグローバル企業の競争力維持を支援します。詳しくは、当社ウェブサイト www.cognizant.com をご覧ください。
雇用に関する追加情報
本募集に記載されている報酬情報は、掲載日時点で正確なものです。Cognizantは、適用される法令に従い、いつでも本情報を変更する権利を留保します。
応募者は、対面またはビデオ会議による面接への参加を求められる場合があります。また、各面接の際に、現在有効な州政府または政府発行の身分証明書の提示を求められる場合があります。
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