Design and implement GenAI solutions using AWS Bedrock and Agentcore.
Define architecture for LLM-based applications, including RAG pipelines and agentic workflows.
Develop and orchestrate agentic AI workflows, enabling multi-step reasoning, tool usage, and task automation.
Build and manage RAG pipelines, including embeddings, retrieval mechanisms, and vector databases.
Integrate LLM capabilities into enterprise applications via APIs and backend services.
Design and optimize prompt engineering strategies for accuracy, relevance, and performance.
Work with structured and unstructured data sources to enable knowledge-driven AI applications.
Ensure model evaluation, monitoring, and optimization for latency, cost, and response quality.
Collaborate with application, data, and platform teams for end-to-end solution delivery.
Define best practices for security, governance, and responsible AI usage.
Troubleshoot and resolve issues in production GenAI systems.
Provide technical leadership and mentor team members while remaining hands-on.

8+ years of relevant hands-on technical experience implementing and developing cloud solutions on AWS.
Hands-on experience on AWS services.
Proven experience using AWS Sagemaker and Bedrock leveraging different types of data sources, Training jobs, real-time and batch applications.
Design and implement agentic AI architectures using frameworks such as LangChain, Strand Agents etc.
Hands-on experience with Amazon AgentCore for building, deploying, and scaling production-grade agentic AI applications.
Architect and deploy scalable AI solutions on AWS, leveraging services like Lambda, Bedrock, Step Functions, S3, API Gateway and SageMaker.
Proficiency in working with LLM APIs (e.g., Claude, Nova, and other third-party LLM providers).
Hands-on experience fine-tuning or optimizing large language models (LLM).
Familiarity with LLM tool use, prompt templating, and context management.
Strong expertise in Vector Databases.
Experience with at least one of the workflow orchestration tools, Airflow, StepFunctions, SageMaker Pipelines, Kubeflow etc.
Ability to collaborate with cross-functional teams such as Developers, QA, Project Managers and other stakeholders.

Join one of the world’s fastest-growing AI-first digital engineering companies and make a real impact at scale.
Lead and collaborate with a high-energy team of talented, driven individuals solving complex, meaningful challenges.
Work with Fortune 500 companies and disruptive innovators in a research-driven environment with 60+ patents.
Stay ahead of the curve by gaining hands-on experience with cutting-edge AI, ML, data, and cloud technologies while continuously upskilling.

GenAI Architect

Key skills