Job description:
Experienced AWS Agentic AI Engineer to design, build, and deploy autonomous and semi‑autonomous AI agents on AWS. This role focuses on developing goal‑driven, tool‑using, multi‑step AI systems capable of reasoning, planning, executing actions, and collaborating with humans and enterprise systems to solve real‑world business problems.
The position sits at the intersection of Large Language Models (LLMs), cloud‑native architecture, APIs, and automation, delivering production‑grade agentic AI solutions using AWS AI/ML and cloud services.
Experience & Qualifications
- Bachelor’s degree in computer science, Engineering, Technology, or a related field, with 8–12 years of overall IT experience and at least 3+ years of hands‑on experience building agentic AI solutions using AWS cloud‑native services.
- Strong expertise in core AWS services including AWS Lambda, Step Functions, EventBridge, S3, DynamoDB or Aurora, OpenSearch, Amazon Bedrock, and Amazon SageMaker.
- Advanced proficiency in Python for building scalable AI systems and automation workflows.
- Proven experience leading the technical design and implementation of complex AI agent architectures and components.
- Hands‑on experience designing Retrieval Augmented Generation (RAG) solutions and applying model fine‑tuning techniques.
- Demonstrated ability to manage performance, scalability, reliability, and cost optimization of AI workloads in production environments.
- Proven experience conducting code reviews, leading knowledge‑sharing sessions, and making critical decisions on technologies, architectures, and frameworks.
- Healthcare domain experience is desirable, along with knowledge of AI safety, governance, compliance, and responsible AI practices.
- AWS certifications such as Solutions Architect or Machine Learning Specialty are preferred, and experience with LangChain and LangGraph is a plus.
- Excellent communication skills with a strong ability to collaborate effectively with both technical and non‑technical stakeholders.
Roles & Responsibilities
- Design and develop agentic AI systems using Amazon Bedrock and other foundation models, including Claude and Titan.
- Build autonomous and semi‑autonomous AI agents capable of multi‑step reasoning, planning, tool usage, action execution, and human‑in‑the‑loop collaboration.
- Integrate with Amazon SageMaker for custom model training, fine‑tuning, evaluation, and experimentation.
- Implement Retrieval Augmented Generation (RAG) solutions using Amazon OpenSearch, Amazon Aurora, DynamoDB, and vector databases such as FAISS or Pinecone.
- Optimize inference cost, latency, scalability, and reliability across AI workloads.
- Implement guardrails, validation layers, and human‑in‑the‑loop controls to ensure safe, reliable, and predictable AI behavior.
- Address hallucination mitigation, prompt injection risks, bias concerns, and model misuse scenarios.
- Ensure compliance with enterprise AI governance, security, and regulatory standards.
- Implement comprehensive logging, monitoring, observability, and audit trails for AI systems.
- Support production deployments, incident resolution, and root cause analysis for AI services.
- Continuously improve agent performance, reliability, robustness, and usability through iteration, monitoring, and feedback.
- Collaborate closely with architecture, DevOps, data engineering, security, and business teams to deliver end‑to‑end AI solutions.
コグニザントについて
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ーとして、お客様にフルスタックのAIソリューションを構築することで、AI投資と企業価値を結ぶ架け橋となっています。業界、ビジネスプロセス、エンジニアリングに関する当社の深い専門知識を活かし、組織固有のビジネス環境をテクノロジー・システムに組み込みます。これにより、人間の可能性を最大限に引き出し、確かな成果を実現するとともに、急速に変化する世界においてグローバル企業が常に一歩先を行くための支援を行っています。 詳細については、cognizant.ai 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。
Cognizantは機会均等雇用主です。応募および選考において、人種、肌の色、性別、宗教、信条、性的指向、性自認、国籍、障がい、遺伝情報、妊娠、退役軍人の地位、その他連邦法・州法・地方自治体の法律により保護されるいかなる特性に基づく差別も行いません。
