Description

Design and own enterprise-scale AI architectures, integrating intelligent systems into existing business platforms and leading solution lifecycles from whiteboard to production.

This role is on-site.

Responsibilities

• Architect multi-layered AI solutions spanning agent orchestration, MCP servers, LLM integrations, and RAG pipelines.
• Lead pre-sales engagements, translating complex AI concepts into business value propositions for executive audiences.
• Define standards, patterns, and best practices for AI architecture, guiding implementation teams through production challenges.
• Evaluate and select AI technologies, models, and cloud services based on business requirements, cost, and governance.
• Mentor technical teams in agentic AI design, multi-model integration, and responsible AI practices.

Required Skills

• 8+ years in enterprise software architecture with 3+ years focused on AI/ML solutions at scale.
• Deep knowledge of generative AI, agentic AI systems, and traditional machine learning (supervised/unsupervised, MLOps).
• Hands-on experience with LLMs including selection, fine-tuning, prompt engineering, and lifecycle management.
• Proficiency in agent orchestration frameworks (LangGraph, AutoGen, CrewAI) and MCP protocol-based integrations.
• Experience with vector databases (Pinecone, Weaviate, pgvector, Chroma) and semantic search architecture.
• Proven track record with major cloud AI platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI).
• Ability to benchmark and select frontier and open-source models (Anthropic, OpenAI, Google, Meta) for production contexts.
• Experience integrating AI with enterprise platforms such as Salesforce, SAP, ServiceNow, or Microsoft 365.

Preferred Skills

• Strong pre-sales capability with experience leading solution workshops and responding to RFPs.
• Familiarity with AI governance, model risk management, bias detection, and explainability frameworks.

Key Skills

Education

Any Gradute