Job 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 : 4- 6 years

Location : Remote

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 :

- 4- 6 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