Description

Define enterprise AI strategy, architecture roadmaps, and scalable GenAI solutions for complex business requirements.

This role is on-site.

Responsibilities

• Design and implement scalable Generative AI architectures, including RAG patterns and intelligent automation systems.
• Lead AI platform governance, security initiatives, and responsible AI practices across cloud environments.
• Architect enterprise integrations using API and microservices patterns, ensuring robust performance and scalability.
• Mentor engineering teams and provide technical leadership on LLM deployment and MLOps best practices.
• Collaborate with stakeholders to translate business needs into actionable AI solution designs.

Required Skills

• 5+ years of experience in AI/ML solution design and implementation.
• Deep expertise in Large Language Models (LLMs) and Generative AI frameworks.
• Hands-on experience with OpenAI, Azure OpenAI, or Amazon Bedrock APIs.
• Proficiency in RAG architectures and vector databases (e.g., Pinecone, Weaviate, FAISS).
• Strong background in cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).
• Experience with AI orchestration tools such as LangChain, LlamaIndex, or Semantic Kernel.
• Solid understanding of enterprise integration patterns, microservices, and API design.
• Bachelor's degree in Computer Science or related field.

Preferred Skills

• Experience with MLOps pipelines and AI governance frameworks.
• Knowledge of Anthropic, Gemini, or other emerging LLM providers.

Key Skills

Education

Bachelor's degree