Agentic AI Solution Designer

Job Summary:

Key Responsibilities:

1. Design, architect, and implement

   agentic AI solutions

   using AWS Bedrock and other AI/LLM platforms.
2. Evaluate and integrate

   open-source agentic frameworks

   such as LangChain, Haystack, or similar.
3. Provide solution design and guidance across

   multi-cloud and hyperscaler environments

   (e.g., Azure OpenAI, Google Vertex AI).
4. Collaborate closely with client-facing teams to understand business requirements and translate them into technical architecture.
5. Act as a

   trusted technical advisor

   in client engagements, presenting designs and roadmaps clearly to both technical and non-technical stakeholders.
6. Ensure scalability, security, and performance of AI solutions in enterprise-grade environments.
7. Stay current with the latest developments in agentic AI, foundation models, and orchestration frameworks.
8. Contribute to internal knowledge sharing, frameworks, and reusable components.

Required Skills Qualifications:

1. 5+ years

   of experience in AI/ML solution design, with recent focus on

   agentic AI architecture

   .
2. Deep hands-on experience with

   AWS Bedrock

   including working with FMs (e.g., Anthropic, Titan, Meta).
3. Familiarity with agentic AI orchestration using

   LangChain, Semantic Kernel, Haystack

   , etc.
4. Experience with

   LLMOps

   , prompt engineering, vector databases (e.g., Pinecone, FAISS), and retrieval-augmented generation (RAG).
5. Strong understanding of

   cloud-native AI services

   across AWS, Azure, and GCP.
6. Proven ability to

   engage with clients

   , articulate complex solutions, and deliver in high-stakes environments.
7. Excellent verbal and written

   communication skills

   ; must be confident, vocal, and collaborative.
8. Bachelor s or Master s in Computer Science, Data Science, AI, or related field.

Preferred Qualifications:

1. AWS certification (e.g.,

   AWS Certified Machine Learning - Specialty

   or

   Solutions Architect

   ).
2. Experience with containerized deployment (Docker, Kubernetes) and MLOps pipelines.
3. Prior consulting or client-delivery experience in an enterprise or digital transformation setting.