Job Title: AI/ML Engineer – Agentic AI

Technical Skill Set

1. Core Programming Skills

- Solid expertise in Python for machine learning, orchestration, and agent development.
- Knowledge of asynchronous programming, concurrency, and task scheduling.

2. Agentic AI

- Experience designing autonomous AI agents for multi-step reasoning, planning, and task orchestration.
- Knowledge of ReAct, Plan-and-Execute, and multi-agent architectures.
- Experience building tool-augmented and function-calling agents.
- Understanding of agent memory management and stateful workflows.

3. Large Language Models (LLMs)

- Hands-on experience with OpenAI, Azure OpenAI, Anthropic, or open-source LLMs.
- Strong prompt engineering skills, including few-shot and zero-shot prompting.
- Understanding of model selection, latency, cost, and context management.
- Knowledge of fine-tuning and LoRA is an advantage.

4. Agent Frameworks

- Hands-on experience with LangGraph and LangChain.
- Familiarity with Semantic Kernel, AutoGen, CrewAI, or similar frameworks.
- Ability to develop custom agent orchestration workflows.

5. RAG, Memory, and Knowledge Management

- Experience implementing Retrieval-Augmented Generation (RAG).
- Knowledge of vector databases such as FAISS, Pinecone, or Azure AI Search.
- Experience with embeddings, document chunking, and context management.
- Knowledge of knowledge graphs or hybrid memory systems is an advantage.

6. Planning and Reasoning

- Experience implementing task planning, replanning,



and self-correction workflows.
- Knowledge of guardrails, action validation, failure detection, and recovery mechanisms.

7. MLOps and AgentOps

- Experience deploying AI agents in production environments.
- Knowledge of agent tracing, logging, monitoring, and prompt/model versioning.
- Experience with CI/CD, Docker, Kubernetes, or serverless deployments.

8. Evaluation and Testing

- Ability to evaluate agent performance based on accuracy, task success, latency, cost, and reliability.
- Experience with testing frameworks, simulation environments, and prompt evaluation.

9. Security and Responsible AI

- Understanding of prompt injection, jailbreak prevention, and secure tool execution.
- Knowledge of data privacy, access control, and responsible AI practices.
- Experience implementing human-in-the-loop workflows.

10. Data and Integration

- Experience integrating AI agents with enterprise systems, APIs, databases, and SaaS platforms.
- Working knowledge of SQL/NoSQL databases and event-driven systems.

11. Cloud Platforms

- Strong experience with Azure, AWS, or GCP.
- Knowledge of managed AI services, identity and access management, secrets management, and cost optimization.
- Azure experience is preferred.

12. Good to Have

- Experience building enterprise copilots and autonomous workflows.
- Multi-agent collaboration and orchestration experience.
- Knowledge of reinforcement learning for agent optimization.

📌 AIML Engineer - Agentic AI (Hyderabad)
🏢 Prophecy Technologies
📍 Hyderabad