Senior AI Architect AI, GenAI & Agentic AI

Role: Senior AI Architect AI, GenAI & Agentic AI (with Context Engineering Expertise)

Role Overview

We are looking for a Senior AI Architect to guide enterprise customers through current-state vs future-state AI transformations. The ideal candidate has deep expertise in context engineering designing and orchestrating context-aware AI systems and a proven track record of building enterprise-grade AI, GenAI, and Agentic AI solutions.

This role blends strategic advisory (gap analysis, roadmaps, executive communication) with hands-on technical architecture (context pipelines, orchestration frameworks, and governance).

Key Responsibilities

Advisory & Gap Analysis

• Conduct AI maturity and readiness assessments, covering infrastructure, data, model lifecycle, and context engineering practices.
• Perform gap analysis of current-state AI/GenAI systems vs desired future-state capabilities (e.g., from single-model solutions to context-rich multi-agent ecosystems).
• Recommend AI adoption roadmaps aligned with business outcomes, ROI, and compliance needs.

Context Engineering & AI Enablement

• Architect context engineering frameworks that unify structured, semi-structured, and unstructured enterprise knowledge into usable context for LLMs and agentic systems.
• Build real-time context pipelines (ingestion, enrichment, retrieval, orchestration) to reduce latency and improve accuracy.
• Define context interfaces/APIs to enable consumption of enterprise knowledge across AI agents, applications, and workflows.
• Implement guardrails, policy layers, and context redaction modules to ensure security, compliance, and ethical AI usage.

Enterprise-Grade AI Architecture

• Design scalable architectures for AI/GenAI/Agentic AI across cloud and hybrid environments (AWS, Azure, Google Cloud Platform).
• Integrate LLMs with vector databases, knowledge graphs, and real-time context stores.
• Lead multi-agent system design (LangGraph, MCP, AutoGen, custom orchestration) to enable autonomous workflows.
• Ensure compliance with enterprise governance frameworks (HIPAA, FDA, GDPR, Part 11/820, HITRUST).

Strategy, Innovation & Customer Advisory

• Run executive workshops and clearly articulate the value of context-aware AI architectures.
• Build maturity models for context engineering adoption and measure business impact.
• Stay ahead of the curve in Agentic AI, contextual orchestration, and self-healing AI systems.
• Contribute to whitepapers, thought leadership, and reference architectures for enterprise customers.

Qualifications & Experience

• Education: Bachelor s/master s in computer science, AI/ML, Data Science, or related; PhD a plus.

Experience:

• 10+ years in AI/ML and enterprise architecture.
• 3+ years with LLMs, GenAI platforms, and orchestration frameworks.
• Proven ability to lead context engineering initiatives in large enterprises.

Technical Expertise:

• Context Engineering: pgvector, Pinecone, Redis, Weaviate, Milvus, knowledge graphs, context layering techniques.
• AI/GenAI: OpenAI, Anthropic, LLaMA, Hugging Face, fine-tuning, RAG pipelines, policy/guardrail frameworks.
• Agentic AI: LangChain, LangGraph, MCP, AutoGen, custom orchestration.
• Enterprise Systems: Integrations with ERP, CRM, EMR/EHR, ServiceNow, etc.
• MLOps & Governance: MLflow, Kubeflow, ModelOps pipelines, Responsible AI frameworks, explainability tools (SHAP, LIME).

Key Competencies

• Visionary strategist who can map current-state vs future-state AI for enterprises.
• Hands-on architect with experience building context-aware, real-time AI ecosystems.
• Strong executive advisory skills with ability to influence at CxO level.
• Ability to balance innovation with compliance in regulated industries.