Agentic AI Engineer

Advance Career Solutions; India; On-site; INR 4,200,000 - 7,000,000; Full time

Job summary

SONOVA AG seeks an experienced Agentic AI Engineer to design, develop, and deploy autonomous AI systems powered by LLMs, Generative AI, AI Agents, and multi-agent frameworks. You will enable reasoning, planning, tool usage, workflow orchestration, and autonomous execution of complex enterprise business processes.

The role emphasizes building AI agents, integrating tools, and delivering scalable AI platforms with MLOps practices.

Qualifications

• Strong expertise in Generative AI and Large Language Models (LLMs).
• Strong understanding of Agentic AI and AI Agent architectures.
• Strong knowledge of Prompt Engineering.
• Hands-on experience with Retrieval-Augmented Generation (RAG).
• Experience designing AI agent workflows and orchestration.

Responsibilities

• Design and develop autonomous AI Agents capable of task execution and decision-making.
• Build single-agent and multi-agent systems for enterprise use cases.
• Develop agent orchestration frameworks, memory architectures, and planning mechanisms.
• Implement tool calling, function calling, and API integrations for AI agents.
• Design agent workflows for customer support, knowledge management, automation, and business operations.

Skills

Generative AI & LLMs

Agentic AI

Prompt Engineering

RAG architecture

AI agent workflows

Tools

LangChain

LangGraph

Semantic Kernel

AutoGen

CrewAI

OpenAI APIs

Azure AI Services

Job description

Job Description Agentic AI Engineer

Job Title

Experience:8–12 Years

Job Summary

SONOVA AG is looking for an innovative Agentic AI Engineer to design, develop, and deploy autonomous AI systems powered by Large Language Models (LLMs), Generative AI, AI Agents, and Multi-Agent frameworks.

The ideal candidate will have strong hands‑on experience building intelligent agents capable of reasoning, planning, tool utilization, workflow orchestration, decision-making, and autonomous execution of complex enterprise business processes.

Key Responsibilities

AI Agent Development

• Design and develop autonomous AI Agents capable of task execution and decision-making.
• Build single-agent and multi-agent systems for enterprise use cases.
• Develop agent orchestration frameworks, memory architectures, and planning mechanisms.
• Implement tool calling, function calling, and API integrations for AI agents.
• Design agent workflows for customer support, knowledge management, automation, and business operations.

LLM & Generative AI Engineering

• Integrate and optimize LLMs such as GPT, Claude, Gemini, Llama, and Mistral.
• Develop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge repositories.
• Build prompt engineering frameworks and implement AI guardrails.
• Fine-tune and evaluate LLM performance for domain-specific use cases.
• Develop conversational AI solutions and intelligent assistants.

AI Platform, MLOps & LLMOps

• Design scalable AI architectures for production deployment.
• Build CI/CD, MLOps, and LLMOps pipelines for AI models and agent lifecycle management.
• Monitor agent performance, hallucinations, accuracy, latency, and operational metrics.
• Implement AI model governance, security, compliance, and responsible AI practices.
• Support cloud-native deployment of AI workloads.

Enterprise Integration

• Integrate AI agents with enterprise platforms such as Salesforce, SAP, ServiceNow, Microsoft 365, CRM, ERP, and custom applications.
• Develop API-based integrations and workflow automation.
• Connect AI agents with structured and unstructured enterprise data sources.

Required Skills

Generative AI & Agentic AI

• Strong expertise in Generative AI and Large Language Models (LLMs).
• Strong understanding of Agentic AI and AI Agent architectures.
• Strong knowledge of Prompt Engineering.
• Hands‑on experience with RAG architecture.
• Experience designing AI agent workflows and orchestration.

AI Frameworks

Hands‑b…">?? Wait truncated?

• LangChain
• LangGraph
• Semantic Kernel
• AutoGen
• CrewAI

AI APIs & Cloud

• OpenAI APIs
• Azure AI Services
• Experience with AI platforms on Azure, AWS, or GCP.

Programming & Integration

• Strong Python programming skills.
• Experience developing and consuming REST APIs.
• Strong understanding of JSON and SQL.
• Experience with API integrations and enterprise application connectivity.

Vector Databases

Experience with one or more:

• Pinecone
• ChromaDB
• Weaviate
• FAISS

Preferred Skills

• Experience building multi-agent ecosystems.
• Knowledge of MLOps and LLMOps practices.
• Experience with Azure AI Foundry.
• Familiarity with Microsoft Copilot Studio and enterprise AI platforms.
• Knowledge of AI security, governance, compliance, and Responsible AI.
• Experience designing production-grade AI systems with monitoring and observability.

Candidate Profile

• Experience: 8–12 Years
• Strong hands‑on experience in Generative AI, LLMs, and Agentic AI.
• Proven experience building and deploying AI agents or multi-agent systems.
• Strong Python and API development skills.
• Experience with RAG, vector databases, and LLM orchestration.
• Experience deploying AI solutions in enterprise or production environments.
• Strong understanding of AI architecture, security, governance, and scalability.