AI Architect

• Proven experience with major cloud AI platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI) and associated infrastructure services

Required Experience

• 8+ years in enterprise software architecture, with at least 3+ years focused on AI/ML solutions at scale
• Deep knowledge of generative AI, agentic AI systems, and traditional machine learning, including:

• Large Language Models (LLMs) – selection, fine-tuning, prompt engineering, and lifecycle management
• Agentic AI design – agent orchestration, tool use, multi-agent coordination, and MCP server configuration
• RAG (Retrieval-Augmented Generation) – vector databases, embedding models, document grounding, and hybrid search
• Traditional ML – supervised/unsupervised learning, model training pipelines, and MLOps practices

• Hands-on multi-model experience—selecting, integrating, and orchestrating frontier and open-source models including:

• Anthropic Claude (e.g., Claude Sonnet, Claude Opus) for reasoning and complex language tasks
• OpenAI GPT series for generative and agentic use cases
• Google Gemini for multimodal and large context window applications
• Meta Llama and other open-source models for on-premise or cost-optimized deployments
• Ability to benchmark, evaluate, and select the right model for the right task in a production context

• Proven experience with major cloud AI platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI) and associated infrastructure services
• Experience integrating AI solutions with enterprise platforms such as Salesforce, SAP, ServiceNow, Microsoft 365, or similar
• Demonstrated track record of successfully translating AI architectures into delivered, production-grade solutions
• Strong pre-sales capability—experience leading solution workshops, responding to RFPs, and presenting to senior decision-maker