We are looking for an Agentic AI Developer with strong hands-on experience in Python, LLM application development, AI agents, evaluation frameworks, and up-to-date GenAI technologies. The candidate will design and develop AI agents capable of reasoning, tool usage, workflow orchestration, retrieval, planning, and autonomous task execution. The role requires a strong engineering mindset with emphasis on reliability, evaluation, observability, and production readiness.

Key Responsibilities

- Design and develop AI agents and multi-agent workflows.

- Build LLM-powered applications using Python.

- Develop agentic workflows involving planning, reasoning, tool calling, memory, and orchestration.

- Integrate LLMs through APIs and model-serving frameworks.

- Develop RAG-based applications using vector databases and retrieval pipelines.

- Design tools and APIs that can be invoked by AI agents.

- Build and maintain agent state, memory, context, and workflow management.

- Implement structured outputs, function calling, guardrails, and validation mechanisms.

- Develop comprehensive LLM/AI evaluation frameworks.

- Create evaluation datasets, test cases, benchmarks, and quality metrics.

- Evaluate model outputs for accuracy, relevance, groundedness, safety, consistency, and task completion.

- Implement automated regression testing for AI applications.

- Monitor production AI systems and identify model/application degradation.

- Optimize prompts, workflows, models, latency, and cost.





- Collaborate with product, UX, backend, frontend, and QA teams.

Required Skills

- Strong Python development experience.

- Strong understanding of LLMs and Generative AI.

- Hands-on experience building LLM-powered applications.

- Understanding of AI agents and agentic workflows.

- Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or equivalent.

- Experience with RAG architectures.

- Experience with vector databases such as Pinecone, Weaviate, FAISS, Chroma, Milvus, or equivalent.

- Experience with LLM APIs such as OpenAI, Anthropic, Gemini, or equivalent.

- Understanding of prompt engineering and structured outputs.

- Experience with LLM evaluations / Evals.

- Understanding of evaluation methodologies and metrics for AI applications.

- Experience building APIs using FastAPI, Flask, or equivalent.

- Strong Git and software engineering practices.

Preferred Skills

- Experience with LangSmith, Arize Phoenix, Ragas, DeepEval, Promptfoo, or equivalent evaluation/observability tools.

- Experience with multi-agent systems.

- Experience with MCP or similar tool-integration protocols.

- Experience with AI safety and guardrails.

- Experience deploying AI applications on AWS/Azure/GCP.

- Experience with Docker and Kubernetes.

- Knowledge of ML fundamentals and model evaluation.

- Experience building enterprise AI applications.

📌 Agentic AI Developer (Hyderabad)
🏢 Cloud Angles Digital Transformation
📍 Hyderabad