Role Overview We are seeking a highly experienced
Principal AI Architect with strong hands-on engineering expertise
in modern AI systems, including LLMs, agentic workflows, and
enterprise-scale integrations. This role involves working closely
with clients to understand complex business problems and
translating them into scalable, production-ready AI architectures.
The ideal candidate combines deep technical expertise with
architectural thinking to design, build, and guide the development
of intelligent systems. Key Responsibilities • Engage with clients
and stakeholders to understand business challenges and define
structured problem statements. • Translate business requirements
into scalable, technically feasible AI architectures. • Design
end-to-end AI systems, including data ingestion, retrieval,
reasoning, and orchestration layers. • Architect and implement
Agentic RAG (Retrieval-Augmented Generation) systems. • Design and
develop multi-agent systems using patterns such as planner–
executor architectures. • Build and orchestrate AI-driven workflows
for complex enterprise use cases. • Design and implement stateful
agent systems, including memory architectures (short-term and
long-term memory). • Integrate vector databases (ChromaDB, Milvus,
PGVector) for semantic search and retrieval. • Develop and
integrate knowledge graphs to enhance contextual reasoning. •
Implement LLM guardrails and evaluation frameworks (e.g., RAGAS,
DeepEval) to ensure reliability and performance. • Design data
ingestion pipelines for structured and unstructured enterprise data
sources. • Build modular, maintainable systems using SOLID
principles and best software engineering practices. • Develop and
deploy AI services using microservices-based architectures and
APIs.



• Conduct feasibility studies and architectural analysis
forintegrating AI with legacy systems (e.g., SAP ecosystems). •
Create detailed technical specifications, architecture diagrams,
and design documentation. • Implement observability and tracing
using tools like LangSmith for debugging and monitoring AI
workflows. • Mentorjunior engineers and provide technical
leadership across AI initiatives. Required Skills s Expertise •
Strong proficiency in Python programming. • Deep experience with
LLM systems, prompt engineering, and agentic architectures. •
Hands-on expertise in Agentic RAG systems and retrieval pipelines.
• Experience with vector databases (ChromaDB, Milvus, PGVector). •
Knowledge of LLM evaluation and guardrails frameworks (RAGAS,
DeepEval). • Experience designing multi-agent systems and AI
workflows. • Strong understanding of state management and memory
systems in AI agents. • Experience with LangChain ecosystem and
observability tools (LangSmith). • Solid understanding of
microservices architecture and API-driven systems. • Experience
designing scalable AI architectures for enterprise environments. •
Familiarity with knowledge graph design and integration. • Strong
foundation in Machine Learning and Deep Learning concepts. •
Experience working with AWS and Docker. • Solid problem-solving
and analyticalthinking abilities. • Excellent communication skills
for clientinteraction and technical documentation. Preferred
Qualifications • Experience deploying AI systems in production
environments at scale. • Exposure to enterprise-grade AI system
design (security, scalability, cost considerations). • Familiarity
with distributed systems and cloud-native architectures. • Prior
experience mentoring orleading engineering teams.

📌 Principle AI Architect (Maharashtra)
🏢 Sperton Global AS
📍 Maharashtra