AI/ML Engineer Technical Skill Set (Noida)

AI/ML Engineer Technical Skill Set (Agentic AI Focus) 1. Core Programming & Systems Skills - Python (expert level) for ML, orchestration, and agent logic - Solid understanding of async programming, concurrency, and task scheduling 2. Foundations of Agentic AI - Design and implementation of autonomous AI agents capable of: - Multistep reasoning and planning - Goal decomposition and task orchestration - Dynamic decisionmaking under uncertainty - Experience with agent architectures: - ReAct, PlanandExecute, Reflexive agents - Hierarchical / multiagent systems - Toolaugmented and functioncalling agents - Understanding of stateful vs stateless agents and memory management 3. Large Language Models (LLMs) - Handson experience with LLMs (OpenAI, Azure OpenAI, Anthropic, opensource models) - Promptengineering techniques for: - Reasoning (ChainofThought, SelfReflection) - Planning and critique loops - Instruction following and tool use - Experience with: - Fewshot and zeroshot prompting - Model selection tradeoffs (latency, cost, context length) - Knowledge of finetuning / adapters (LoRA) is a plus 4. Agent Frameworks & Tooling - Practical experience with agent frameworks, such as: - LangGraph / LangChain (agents, tools, memory) - Semantic Kernel - AutoGen, CrewAI, or similar - Ability to build custom agent orchestration layers beyond frameworks - Tool abstraction and execution safety (timeouts, retries, sandboxing) 5. Memory, Context & Knowledge Augmentation - Design of agent memory systems: - Shortterm (conversation/state memory) - Longterm (episodic, semantic memory) - RetrievalAugmented Generation (RAG): - Vector databases (FAISS, Pinecone, Azure AI Search, etc.) - Embedding selection and chunking strategies - Techniques for context management and compression - Knowledge graphaugmented or hybrid memory (plus) 6. Planning, Reasoning & Control - Experience implementing: - Task planners (step planning, replanning) - Constraintbased execution - .