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.
- Robust 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.

- Strong 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 (Nashik)
🏢 Sperton Global AS
📍 Nashik