Senior AI Integration Architect

Job Summary: The Senior AI Integration Architect serves as the bridge between model capabilities and enterprise infrastructure. You will design agentic workflows, complex RAG architectures, and API middleware that connect fine-tuned SLMs directly to legacy software platforms (ERPs, CRMs, core banking systems).

Key Responsibilities

- Agentic System Engineering: Design multi-agent workflows (using LangChain, LlamaIndex, AutoGen, or Semantic Kernel) that execute tasks by invoking enterprise APIs.
- Advanced RAG & Vector Systems: Build enterprise Retrieval-Augmented Generation (RAG) pipelines with hybrid vector/text search, contextual re-ranking, and energetic chunking.
- Systems & Middleware Integration: Build secure REST/gRPC connectors, webhooks, and middleware to bridge SLMs with legacy systems like SAP, Oracle, Salesforce, and core banking backends.
- Enterprise Security & Privacy: Implement role-based access control (RBAC), data loss prevention (DLP),



and PII redactors to ensure client data remains fully secure.

Mandatory Skills (Must-Haves)

- Agentic Frameworks: Hands-on mastery of LangChain, LlamaIndex, or AutoGen for orchestrating complex tool-calling workflows.
- Vector Databases & RAG: Expert-level knowledge of vector databases (Qdrant, Pinecone, Milvus, or pgvector) and hybrid search strategies.
- Enterprise Integration Paradigms: Proficiency in API management (REST, GraphQL, gRPC), messaging queues (Apache Kafka, RabbitMQ), and microservices architecture.
- Secure Software Development: Proven ability to implement PII masking, tokenization, and enterprise identity standards (OAuth 2.0, SAML, RBAC).
- Backend Engineering: Advanced proficiency in Python or TypeScript/Node.js for backend service construction.

📌 Integration Architect (Noida)
🏢 Bharat It Services
📍 Noida