Agentic AI Solution Designer

We are seeking a highly skilled and proactive Agentic AI Solution Designer to join our cutting-edge AI and cloud innovation team. You will be responsible for designing and implementing robust, scalable AI systems using AWS Bedrock and agentic frameworks, while also showcasing flexibility in working with open-source and multi-cloud platforms. This role requires you to be a trusted technical advisor, collaborating closely with client-facing teams to translate business requirements into effective technical architectures.

Roles & Responsibilities:

• Design, architect, and implement agentic AI solutions using AWS Bedrock and other AI/LLM platforms.
• Evaluate and integrate open-source agentic frameworks such as LangChain, Haystack, or similar.
• Provide solution design and guidance across multi-cloud and hyperscaler environments (e.g., Azure OpenAI, Google Vertex AI).
• Collaborate with client-facing teams to understand business requirements and translate them into a technical architecture.
• Act as a trusted technical advisor in client engagements, presenting designs and roadmaps clearly to both technical and non-technical stakeholders.
• Ensure the scalability, security, and performance of AI solutions in enterprise-grade environments.
• Stay current with the latest developments in agentic AI, foundation models, and orchestration frameworks.
• Contribute to internal knowledge sharing, frameworks, and reusable components.

Skills Required:

• Deep hands-on experience with AWS Bedrock, including working with foundation models (FMs) like Anthropic, Titan, and Meta.
• Familiarity with agentic AI orchestration using LangChain, Semantic Kernel, Haystack, etc.
• Experience with LLMOps, prompt engineering, vector databases (e.g., Pinecone, FAISS), and retrieval-augmented generation (RAG).
• Strong understanding of cloud-native AI services across AWS, Azure, and GCP.
• Proven ability to engage with clients and articulate complex solutions.
• Excellent verbal and written communication skills, with a confident and collaborative approach.
• AWS certification (e.g., AWS Certified Machine Learning - Specialty or Solutions Architect) is a plus.
• Experience with containerized deployment (Docker, Kubernetes) and MLOps pipelines is a plus.
• Prior consulting or client-delivery experience is a plus.

QUALIFICATION:

• Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field.