AI Engineer
Job Summary
We are seeking an experienced AI Engineer to design, build, and deploy production-grade agentic AI solutions for enterprise-scale use cases. The ideal candidate will have strong hands-on experience with Agent-to-Agent frameworks, Model Context Protocol integrations, AI/ML engineering, cloud-native architecture, and Azure-based deployment. This role requires a strong engineering mindset, the ability to build scalable and reliable AI systems, and effective communication with technical and non-technical stakeholders.
Roles and Responsibilities
· Design, build, and maintain multi-agent AI systems using Agent-to-Agent frameworks, including agent roles, communication contracts, orchestration patterns, and lifecycle management.
· Implement and enhance Model Context Protocol integrations to support standardized context sharing, memory management, and tool access across distributed AI pipelines.
· Develop embedding pipelines, prompt engineering strategies, and context engineering approaches for retrieval-augmented generation and LLM-based applications.
· Build production-grade AI services, ML inference wrappers, APIs, and asynchronous components using Python, Java, and/or Go.
· Deploy and manage scalable AI workloads on Azure using Azure Functions, Azure Container Apps, API Management, Event Grid, Service Bus, and related cloud services.
· Design and optimize data and storage solutions using Azure AI Search, Redis, Cosmos DB, Blob Storage, and related vector or caching technologies.
· Apply cloud-native architecture principles to ensure scalability, resiliency, performance optimization, observability, and cost efficiency across AI platforms.
· Collaborate with engineering, product, data science, and DevOps teams to deliver reliable AI solutions, technical documentation, architecture decisions, and stakeholder updates.
Required Qualifications
· Hands-on experience with Agentic Layer, Agent-to-Agent frameworks, and Model Context Protocol.
· Strong AI/ML engineering experience, including vector embeddings, prompt engineering, context engineering, and retrieval-augmented generation concepts.
· Strong programming experience in at least two of the following languages: Python, Java, and Go.
· Proven experience deploying cloud-native solutions on Microsoft Azure.
· Experience with Azure AI Search, Redis, Cosmos DB, and related database or vector search technologies.
· Experience designing and managing Azure Functions and Azure Container Apps.
· Strong understanding of cloud-native architecture, scalability, performance optimization, monitoring, and distributed system design.
· Excellent communication skills with the ability to explain complex technical concepts to technical and non-technical stakeholders.
Preferred Qualifications
· Experience with Azure Blob Storage and document ingestion pipelines.
· Exposure to Iceberg-based lakehouse patterns for large-scale training data management or offline AI evaluation datasets.
· Experience with emerging agentic frameworks such as LangGraph, AutoGen, CrewAI, or custom multi-agent frameworks.
· Experience with Infrastructure-as-Code tools such as Bicep, Terraform, or ARM templates.
· Experience with distributed tracing, structured logging, metrics dashboards, load testing, and capacity planning.
Interview and Work Details
· Client interview is required before candidate finalization.
· Client interview availability is Monday through Friday, 9:00 AM to 5:00 PM ET/CT/PT.
Important Disclaimers:
**Please note: A few of our roles may require in-person interviews at Cognizant offices or client locations, depending on project or client needs.**
**Candidate must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future**
Exact work location is Norfolk, VA, USA.
-- We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.
Salary and Other Compensation:
The annual salary for this position is between $81K – $141K depending on experience and other qualifications of the successful candidate.
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.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
- Medical/Dental/Vision/Life Insurance
- Paid holidays plus Paid Time Off
- 401(k) plan and contributions
- Long-term/Short-term Disability
- Paid Parental Leave
- Employee Stock Purchase Plan
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
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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