About the Role
We are seeking an experienced AI Engineer who specialises in delivering end-to-end AI solutions using Agentic AI frameworks and Generative AI technologies. This role demands consultative skills, technical expertise, and the ability to identify impactful use cases and articulate business benefits while implementing scalable AI solutions.
Key Responsibilities
- Design and implement Agentic AI architectures for enterprise workflows.
- Integrate Generative AI capabilities (LLMs, multimodal models) into client solutions.
- Deliver end-to-end AI solutions from ideation to production deployment.
- Build, fine-tune, and evaluate LLM-based Q&A models using frameworks like AWS Bedrock, LangChain, HuggingFace Transformers, or OpenAI API.
- Design prompt templates and implement retrieval strategies to increase answer precision and factuality.
- Assist in creating data pipelines for training and testing, including annotation and evaluation tooling.
- Collaborate with product managers to translate user requirements into technical features.
- Participate in error analysis, iterative model improvement, and performance tuning.
- Document code and workflows clearly; follow best practices for reproducibility and code quality.
- Engage with clients to identify high-value AI use cases and define business benefits.
- Conduct workshops and assessments to align AI strategies with organisational goals.
- Provide thought leadership on AI adoption and emerging trends.
- Develop reusable frameworks and accelerators for Agentic AI and GenAI.
- Ensure compliance with AI ethics, security, and governance standards.
- Mentor junior engineers and guide cross-functional teams.
- Stay ahead of industry developments in Agentic AI, autonomous agents, and LLM ecosystems.
- Develop and deploy autonomous agents using Azure AI Agent Service, ensuring state management, memory persistence, and secure tool execution.
- Orchestrate complex multi-agent workflows to handle tasks requiring planning, reasoning, and tool use.
- Extend Microsoft 365 Copilot by building custom plugins and declarative agents within Microsoft Copilot Studio to surface enterprise data in Teams and Office apps.
- Operationalize AI solutions using Microsoft AI Foundry for model catalog management, Prompt Flow evaluation, and lifecycle governance.
- Architect scalable deployment patterns for agents using Azure Container Apps or Azure Functions, ensuring low-latency responses and cost-effective scaling.
Required Skills :
- Strong experience in Agentic AI frameworks (e.g., LangGraph, AutoGen, CrewAI).
- Hands-on expertise with Generative AI (LLMs, prompt engineering, fine-tuning).
- Proficiency in Python and familiarity with deep learning/NLP libraries (LangChain, PyTorch, TensorFlow, HuggingFace Transformers).
- Experience with building Q&A systems and retrieval-augmented generation pipelines.
- Knowledge of vector databases or semantic search concepts.
- Familiarity with cloud AI platforms (AWS Bedrock, Azure OpenAI, GCP Vertex AI).
- Knowledge of MLOps practices and deployment pipelines.
- Ability to articulate business value of AI solutions and drive client conversations.
- Experience with Git, collaborative development workflows, and cloud infrastructure (AWS, Azure, GCP, Domino).
- Experience building custom copilots and plugins using Microsoft Copilot Studio and integrating them with Power Platform connectors.
- Proficiency in deploying AI workloads to Azure Container Apps (ACA), Azure Kubernetes Service (AKS), or serverless functions (Azure Functions) for event-driven agent triggers.
- Experience implementing RAG using Azure AI Search (vector, semantic, and hybrid search) and OneLake/Microsoft Fabric.
Nice to Have Skills
- Certification: Microsoft Certified: Azure AI Engineer Associate or similar specialized training in Azure OpenAI.
- Experience implementing Azure Managed Identities, Private Endpoints, and Content Safety filters for enterprise-grade agent security.
- Familiarity with tracing agent thought processes (tracing chains/flows) and monitoring token usage in Azure Monitor/App Insights.
Consultative & Business Skills
- Excellent stakeholder management and communication skills.
- Ability to translate technical concepts into business outcomes.
- Experience in workshops, solution roadmaps, and executive presentations.
Education & Experience
Bachelor’s/Master’s in Computer Science, AI/ML, or related discipline (or equivalent experience).
Why This Role Matters
Agentic AI and Generative AI are redefining automation and decision-making. This role offers the opportunity to lead transformative projects that combine autonomous agents, LLM-powered Q&A systems, and consultative expertise to deliver measurable business impact.
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。
Cognizant 是一家提供平等就业机会的雇主。在招聘过程中，您的申请和候选资格不会因种族、肤色、性别、宗教、信仰、性取向、性别认同、国籍、残疾、遗传信息、怀孕、退伍军人身份或任何其他受联邦、州或地方法律保护的特征而受到影响。
