Lead architecture and delivery of AI-first, agentic systems: design LLM integrations, RAG pipelines, multi-agent workflows, Python-based scalable backends, distributed event-driven microservices, and cloud-native solutions; ensure performance, security, cost optimization, and provide technical leadership across engineering and product teams.
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
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