Job Description:

- Build application-facing AI features powered by LLMs, agentic workflows, and AI orchestration platforms.

- Integrate with MLOps-managed agents and consume LLM capabilities through AI

- Gateway patterns including routing, authentication, policy controls, and logging.

- Design and implement agentic workflows using tool calling, function calling,

- context handling, prompt/version management, and orchestration patterns.

- Work with Agentic Layer A2A frameworks and MCP Protocol to enable

- interoperable agent communication and workflow execution.

- Develop RAG-based solutions using vector embeddings, vector databases, Azure

- AI Search, Redis, Cosmos DB, and relevant cloud data stores.

- Build and orchestrate LLM-powered applications using LangChain, LangGraph,

- and related frameworks.





- Deploy scalable AI solutions on Azure using Azure Functions, Azure Container

- Apps, and cloud-native architecture patterns.

- Optimize AI applications for latency, scalability, reliability, cost, and performance.

- Implement production readiness practices including testing, observability,

- monitoring, evaluations, guardrails, safety controls, and incident support.

- Partner with security, compliance, architecture, and platform teams to meet

- governance, data protection, and enterprise control requirements.

- Document integration patterns, architecture, operational runbooks, evaluation

- practices, and reusable engineering components.

📌 AI Engineer (Bengaluru)
🏢 Acme Services Private
📍 Bengaluru