12 hours ago
Dallas, TX, USASenior / Staff+
H1B sponsor
Responsibilities
- Design and develop autonomous and semi-autonomous agentic AI systems using Amazon Bedrock and foundation models such as Claude and Titan.
- Build multi-step AI agents with reasoning, planning, tool usage, action execution, and human-in-the-loop collaboration.
- Integrate Amazon SageMaker for custom model training, fine-tuning, evaluation, and experimentation.
- Implement RAG solutions using Amazon OpenSearch, Amazon Aurora, DynamoDB, and vector databases such as FAISS or Pinecone.
- Optimize AI workloads for inference cost, latency, scalability, reliability, and production performance.
- Implement guardrails, validation layers, and human-in-the-loop controls to improve AI safety and predictability.
- Address hallucination mitigation, prompt injection, bias, model misuse, governance, security, and regulatory compliance.
- Implement logging, monitoring, observability, and audit trails for AI systems.
- Support production deployments, incident resolution, and root cause analysis for AI services.
- Collaborate with architecture, DevOps, data engineering, security, and business teams to deliver end-to-end AI solutions.
Requirements
- Bachelor's degree in computer science, engineering, technology, or a related field.
- 8–12 years of overall IT experience, including at least 3 years of hands-on experience building agentic AI solutions using AWS cloud-native services.
- Strong expertise in AWS Lambda, Step Functions, EventBridge, S3, DynamoDB or Aurora, OpenSearch, Amazon Bedrock, and Amazon SageMaker.
- Advanced Python proficiency for scalable AI systems and automation workflows.
- Experience leading the technical design and implementation of complex AI agent architectures and components.
- Hands-on experience designing RAG solutions and applying model fine-tuning techniques.
- Experience managing performance, scalability, reliability, and cost optimization of production AI workloads.
- Experience conducting code reviews, leading knowledge-sharing sessions, and making decisions about technologies, architectures, and frameworks.
- Excellent communication and collaboration skills with technical and non-technical stakeholders.
- Healthcare domain experience and knowledge of AI safety, governance, compliance, and responsible AI practices are desirable.
- AWS Solutions Architect or Machine Learning Specialty certifications are preferred.
- Experience with LangChain and LangGraph is a plus.
Benefits
- Hybrid work arrangement.
Categories
About Cognizant
Cognizant is a public IT services and consulting firm that designs, builds, and runs enterprise technology, including digital engineering, cloud modernization, data/AI, and managed services. It sells consulting, systems integration, and outsourcing on multi-year engagements to large enterprises in healthcare, banking, retail, communications, and manufacturing. Founded in 1994 and headquartered in Teaneck, New Jersey, Cognizant is NASDAQ-listed (CTSH) and a Fortune 500 company.