- Location
- Hyderabad
- Workplace
- Hybrid
- Type
- Full-time
- Department
- Engineering
- Experience
- 5+ years
- Closing date
- Today
- Source
- CareersPage
Description
We are looking for an AI Engineer specializing in Agentic AI systems and cloud-native deployment. This role focuses on building intelligent, autonomous systems using LLMs, RAG architectures, and emerging protocols like MCP, with an emphasis on scalable, production-ready implementations.
Experience: 5 years - Minimum 5 years of experience is required.
Location: Hybrid - Bengaluru/ Hyderabad/ Pune/ Gurugram
Shift Timings: 12 PM - 9 PM IST
**Looking for immediate joiners only**
Key Responsibilities
- Design and build Agentic AI systems capable of planning, reasoning, and tool usage
- Develop and optimize RAG (Retrieval-Augmented Generation) pipelines for enterprise use cases
- Implement and integrate Model Context Protocol (MCP) or similar frameworks for tool orchestration
- Build multi-agent workflows and autonomous decision-making systems
- Deploy AI applications on cloud platforms (AWS, Azure, GCP) with scalability and reliability
- Develop APIs and services to integrate LLM-powered features into products
- Work with vector databases and retrieval systems for efficient knowledge access
- Optimize latency, cost, and performance of LLM-based applications
- Implement observability, monitoring, and evaluation frameworks for AI systems
- Collaborate with product and engineering teams to deliver production-grade AI solutions
Required Skills & Qualifications
- 5+ years of experience in software engineering or AI engineering roles
- Strong proficiency in Python and modern backend frameworks (FastAPI, Flask, etc.)
- Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, or similar
- Strong understanding of RAG architectures, embeddings, chunking, and retrieval strategies
- Experience with vector databases (Pinecone, Weaviate, FAISS, Chroma, etc.)
- Experience building agentic workflows (tool use, memory, planning, orchestration)
- Familiarity with MCP (Model Context Protocol) or similar tool-interaction paradigms
- Experience deploying AI applications on cloud platforms (AWS/Azure/GCP)
- Strong knowledge of Docker, Kubernetes, and microservices architecture
- Experience designing and consuming REST APIs / async systems
Preferred Qualifications
- Experience with multi-agent systems and orchestration frameworks
- Familiarity with prompt engineering, evaluation, and guardrails
- Knowledge of LLM observability tools (LangSmith, Weights & Biases, etc.)
- Experience with streaming architectures and real-time AI systems
- Exposure to security and governance in AI systems
- Understanding of cost optimization strategies for LLM usage
Soft Skills
- Strong problem-solving and system design skills
- Ability to work in fast-evolving AI landscapes
- Good communication and cross-functional collaboration
Skills
PythonFlaskFastAPIAWSAzureGCPDockerKubernetesRESTMicroservices
