Lead the design and delivery of AI-first, agentic, and distributed systems. Define architecture strategy and guide engineering teams in building scalable, intelligent AI-powered platforms.
Principal Architect – AI / LLM / Agentic Systems
Experience: 12–18 Years
Location: US (Remote/Hybrid)
Role Overview
We are looking for a Principal Architect to lead the design and delivery of AI-first, agentic, and distributed systems. This role requires deep expertise in Python-based architectures, LLM integrations, and cloud-native systems, with the ability to translate complex business problems into scalable, intelligent solutions.
You will define architecture strategy, guide engineering teams, and drive end-to-end solutioning for AI-powered platforms.
Key Responsibilities
Define and drive architecture for AI/LLM-powered systems and agentic workflows
Design RAG pipelines, multi-agent systems, and intelligent orchestration layers
Architect scalable backend systems using Python
Build and guide implementation of distributed, event-driven architectures
Lead cloud-native solution design (AWS / Azure / GCP)
Define system integration patterns across APIs, microservices, and AI services
Ensure performance, scalability, security, and cost optimization
Provide technical leadership, mentoring, and architectural governance
Collaborate with product and business teams to shape solution strategy
Must-Have Qualifications
12+ years of experience in architecture / senior engineering roles
Strong expertise in Python-based system design and development
Hands-on experience with LLMs, RAG architectures, and AI integrations
Experience building agentic systems / multi-agent architectures
Strong understanding of distributed systems and microservices architecture
Experience with cloud platforms (AWS / Azure / GCP)
Expertise in API design, system integration, and scalable backend architectures
Strong problem-solving, system design, and architectural decision-making skills
Good-to-Have
Experience with frameworks like LangChain or LlamaIndex
Exposure to Model Context Protocol (MCP) or similar agent frameworks
Experience with Vector Databases (FAISS, Pinecone, Weaviate)
Knowledge of streaming systems (Kafka, event-driven pipelines)
Experience with DevOps, CI/CD, and platform engineering
What Makes This Role Unique
Opportunity to architect next-gen AI-first platforms and agentic systems
High ownership in defining enterprise-scale AI architecture strategy
Blend of deep tech (AI + distributed systems) and business impact
Work on cutting-edge GenAI use cases in production environments