Agentic AI Manager

Vlink; Mumbai; Vor Ort; INR 1.200.000 - 2.600.000; Vollzeit

Zusammenfassung

Vlink is seeking an AI Agent Architect to design end-to-end agent architectures, build RAG pipelines, and integrate agents with SAP, Snowflake, Microsoft 365, and other enterprise APIs. You will implement MCP servers and tool-calling layers, ensuring scalable, safe, and maintainable agent systems.

You will collaborate with IT, data engineering, and business stakeholders to translate requirements into robust agent solutions, mentoring junior engineers and driving architectural best practices.

Qualifikationen

• Experience designing AI agents and architectures.
• Familiarity with patterns like ReAct and Reflection Pattern.
• Knowledge of tool integration and data access for agents.

Aufgaben

• Design end-to-end AI agent architectures for single-agent and multi-agent systems.
• Develop agents with Python-based frameworks and Copilot Studio connectors.
• Integrate agents with enterprise APIs and data sources (e.g., SAP, SharePoint, Microsoft 365).
• Implement MCP servers to expose tools and data sources to agents.
• Build tool-calling layers for real-time DBs, ERPs, and third-party APIs.
• Establish governance, safety, and audit documentation for agent systems.

Kenntnisse

Python

APIs

Agent architectures

MCP (Model Context Protocol)

Tools

SAP

Snowflake

Microsoft Graph API

SharePoint

Teams

Power Automate

Pinecone

Azure AI Search

ChromaDB

Jobbeschreibung

Key Responsibilities

1. Agent Design & Architecture

• Design end-to-end AI agent architectures including single-agent and multi-agent systems using patterns such as ReAct, Reflection Pattern.
• Define agent goals, tools, MCP, memory strategies (in-context, external, semantic, episodic), and failure-handling logic.
• Select the appropriate agent pattern and framework based on use-case complexity and enterprise constraints
• Build agentic RAG systems combining vector search, semantic retrieval, and LLM reasoning for knowledge-grounded responses

2. Development & Integration

• Develop AI agents using Python-based frameworks for code-first builds
• Build and configure agents on Microsoft Copilot Studio with custom connectors, adaptive cards, and Power Automate flow integrations
• Integrate agents with enterprise APIs: SAP, Snowflake (Cortex), Microsoft Graph API, SharePoint, Teams, and other M365 services etc.
• Implement MCP (Model Context Protocol) servers to expose tools and data sources to agents in a standardized, composable manner
• Build tool-calling layers that allow agents to interact with databases, ERPs, and third-party APIs in real time
• Design human-in-the-loop checkpoints for approval workflows, exceptions, and escalation scenarios

3. RAG & Knowledge Management

• Design and implement Retrieval-Augmented Generation (RAG) pipelines: document ingestion, chunking, embedding, vector store indexing, and context-aware retrieval
• Work with vector databases (Pinecone, Azure AI Search, ChromaDB) to build semantic search capabilities for enterprise knowledge bases
• Implement agentic RAG patterns including query routing, self-reflection, and query reformulation for higher-quality responses

4. Evaluation, Testing & Observability

• Build evaluation frameworks to measure agent accuracy, task completion rate, hallucination rate, and latency
• Implement observability and tracing to debug and improve agent behavior in production
• Define and monitor KPIs for deployed agents; establish feedback loops for continuous improvement
• Conduct structured prompt engineering and system prompt optimization to improve reliability and output quality

5. Governance, Safety & Responsible AI

• Implement guardrails, content filters, and safety mechanisms to ensure agents behave within defined boundaries
• Apply responsible AI principles: fairness, transparency, explainability, and data privacy compliance
• Document agent logic, decision flows, tool schemas, and known limitations for audit and knowledge transfer

6. Collaboration & Stakeholder Management

• Partner with business process owners to translate operational problems into agent design briefs
• Collaborate with IT, data engineering, and enterprise architecture teams for system integration and cloud deployment
• Present agent capabilities, prototypes, and performance reports to senior leadership including CIO-level audiences
• Mentor junior team members and Management Trainees on agent concepts, tools, and development best practices