AI/ML Engineer – Technical Skill Set (Agentic AI Focus)

Remote (USA)
C2C

AI/ML Engineer – Technical Skill Set (Agentic AI Focus)

Location: Remote

  1. Core Programming & Systems Skills
  • Python (expert level) for ML, orchestration, and agent logic
  • Strong understanding of async programming, concurrency, and task scheduling
  1. Foundations of Agentic AI
  • Design and implementation of autonomous AI agents capable of:
  • Multi-step reasoning and planning
  • Goal decomposition and task orchestration
  • Dynamic decision-making under uncertainty
  • Experience with agent architectures:
  • React, Plan-and-Execute, Reflexive agents
  • Hierarchical / multi-agent systems
  • Tool-augmented and function-calling agents
  • Understanding of stateful vs stateless agents and memory management
  1. Large Language Models (LLMs)
  • Hands-on experience with LLMs (OpenAI, Azure OpenAI, Anthropic, open-source models)
  • Prompt-engineering techniques for:
  • Reasoning (Chain-of-Thought, Self-Reflection)
  • Planning and critique loops
  • Instruction following and tool use
  • Experience with:
  • Few-shot and zero-shot prompting
  • Model selection trade-offs (latency, cost, context length)
  • Knowledge of fine-tuning / adapters (LoRA) is a plus
  1. 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)

 

  1. Memory, Context & Knowledge Augmentation
  • Design of agent memory systems:
  • Short-term (conversation/state memory)
  • Long-term (episodic, semantic memory)
  • Retrieval-Augmented Generation (RAG):
  • Vector databases (FAISS, Pinecone, Azure AI Search, etc.)
  • Embedding selection and chunking strategies
  • Techniques for context management and compression
  • Knowledge graph-augmented or hybrid memory (plus)
  1. Planning, Reasoning & Control
  • Experience implementing:
  • Task planners (step planning, re-planning)
  • Constraint-based execution
  • Feedback and self-correction loops
  • Understanding of:
  • Tool reliability scoring
  • Guardrails and action validation
  • Failure detection and graceful recovery
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