Location: Hyderabad (Hybrid)

Employment Type: Full-Time

Experience: 4+ Years

Joining: Immediate Joiners Preferred

About the Role

We are seeking a skilled AI Engineer to design, develop, and deploy enterprise-grade AI and Generative AI solutions. The ideal candidate will have hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, Model Context Protocol (MCP), and modern AI application development. Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP) is preferred.

Key Responsibilities

• Design, build, and deploy AI-powered applications using modern AI technologies.
• Develop and implement Generative AI and LLM-based solutions for enterprise use cases.
• Build Retrieval-Augmented Generation (RAG) applications using vector databases and semantic search.
• Develop AI agents and multi-agent workflows for task automation and intelligent decision-making.
• Integrate AI models with enterprise applications, APIs, databases, and third-party services.
• Develop scalable backend services, AI pipelines, and cloud-native applications.
• Optimize prompts, model performance, inference workflows, and application reliability.
• Deploy, monitor, and maintain AI applications in cloud environments.
• Collaborate with cross-functional teams to deliver secure, scalable, and production-ready AI solutions.
• Follow AI governance, security, and responsible AI best practices.

Technical Skills

AI & Generative AI

• Generative AI and Large Language Models (LLMs)
• Prompt Engineering, Prompt Chaining, Function Calling, Tool Calling
• Structured Outputs, JSON Schema
• Model Evaluation, Guardrails, Fine-tuning concepts

Agentic AI

• AI Agents and Multi-Agent Systems
• Planning and Multi-step Reasoning
• Memory and Context Management
• Tool Orchestration
• Human-in-the-Loop Workflows
• AI Observability

AI Frameworks

Experience with one or more of:

• LangChain
• LangGraph
• Semantic Kernel
• AutoGen
• CrewAI
• LlamaIndex

RAG & Knowledge Systems

• Retrieval-Augmented Generation (RAG)
• Model Context Protocol (MCP)
• Vector Search and Semantic Search
• Hybrid Search
• Embeddings
• Document Processing and Chunking
• Knowledge Grounding
• Citation Generation

Cloud Technologies (Preferred)

Experience with one or more cloud platforms:

• Microsoft Azure
• Amazon Web Services (AWS)
• Google Cloud Platform (GCP)

Experience with AI/ML services, serverless computing, containers, storage, identity management, monitoring, and API management is preferred.

Data & Databases

• SQL and NoSQL databases
• PostgreSQL, MySQL, SQL Server, MongoDB, Cosmos DB, or similar
• Vector databases such as Pinecone, Weaviate, Milvus, Qdrant, Chroma, or Azure AI Search

DevOps & Containers

• Git
• CI/CD pipelines
• Docker
• Kubernetes
• Infrastructure as Code (Terraform is a plus)

Security & Governance

• Responsible AI principles
• Prompt Injection Prevention
• Role-Based Access Control (RBAC)
• Data Privacy and Security
• Secrets Management
• Monitoring and Logging

Preferred Skills

• Experience building production-grade AI applications.
• Experience integrating AI with enterprise platforms such as Microsoft 365, Salesforce, SAP, ServiceNow, Dynamics 365, or similar business applications.
• Familiarity with GraphRAG, Knowledge Graphs, MLflow, Hugging Face, Ollama, open-source LLMs (Llama, Mistral, Gemma, etc.), and AI observability tools.
• Experience with event-driven architectures and messaging platforms such as Kafka or cloud-native messaging services.

📧 Share your updated resume to: [email protected]

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