Agentic AI Solution Designer

Bytespoke Technology Private Limited · 1 week ago
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Location
India - Anywhere
Department
Consulting - IN
Employment Type
Contract

Job Summary:

We are seeking a highly skilled and proactive Agentic AI Solution Designer to join our cutting-edge AI and cloud innovation team. This role demands a strong grasp of AWS Bedrock and agentic AI solutions, while also showcasing flexibility in working with open-source agentic frameworks and other hyperscaler-based AI platforms. The ideal candidate will play a key role in designing and delivering robust, scalable AI systems while working closely with cross-functional delivery teams and clients.

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.