AI Engr II

Hands-on production experience with agent orchestration frameworks such as LangGraph, OpenAI Agents SDK, or equivalent.

Deep understanding of foundational agentic design patterns, including: Reflection Tool Use Planning Multi-Agent Collaboration

Reflection

Tool Use

Planning

Multi-Agent Collaboration

Practical experience with: Function calling Structured outputs Prompt engineering Context window management

Function calling

Structured outputs

Prompt engineering

Context window management

Experience building applications using: Large Language Models (LLMs) Vision Language Models (VLMs) Embedding models

Large Language Models (LLMs)

Vision Language Models (VLMs)

Embedding models

Strong understanding of model capabilities, limitations, and optimization techniques.

Proven ability to develop: Self-healing workflows Automated debugging mechanisms Human-in-the-Loop approval processes Quality assurance and audit checkpoints

Self-healing workflows

Automated debugging mechanisms

Human-in-the-Loop approval processes

Quality assurance and audit checkpoints

Experience deploying Generative AI solutions in: On-premises environments Hybrid architectures Public cloud environments

On-premises environments

Hybrid architectures

Public cloud environments

Hands-on experience in any one of the below cloud platforms : Microsoft Azure AWS Google Cloud Platform (GCP)

Microsoft Azure

AWS

Google Cloud Platform (GCP)

Experience applying data mining and machine learning techniques, including: Decision Trees Neural Networks Support Vector Machines (SVM) Anomaly Detection Recommender Systems Pattern Discovery Text Mining

Decision Trees

Neural Networks

Support Vector Machines (SVM)

Anomaly Detection

Recommender Systems

Pattern Discovery

Text Mining