Lead Python (Full Stack) /AI Developer

Kaav Inc; Phoenix (AZ); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Kaav Inc. seeks a Lead Software Engineer for Full Stack & AI development in Phoenix. You will drive design, architecture, and delivery of intelligent applications powered by Agentic AI, overseeing the full lifecycle from requirements to deployment.

The role requires leadership of technical teams, deep experience in modern web tech (Angular/React/TypeScript) and AI-driven systems, with hands-on work across cloud, containerization, and data technologies.

Qualifications

• 8+ years of professional software engineering experience.
• 3+ years leading technical teams or serving as a lead engineer.
• 2+ years designing and implementing Generative AI or Agentic AI solutions in enterprise environments.
• Experience delivering large-scale enterprise applications from inception through production.

Responsibilities

• Lead the design, development, and delivery of AI-powered, enterprise-scale applications.
• Define architecture, establish engineering standards, and mentor teams.
• Guide implementation of Agentic AI platforms, intelligent workflows, and RAG-based solutions.
• Oversee full lifecycle from requirements through deployment and production support.

Skills

Java

Angular

React

TypeScript

Agentic AI

RAG

Prompt engineering

Semantic search

Cloud platforms

Docker

CI/CD

API design

Distributed systems

Multi-agent orchestration

Tools

Docker

GitHub Actions

CI/CD pipelines

Infrastructure as Code

Cloud services

Job description

Job Title: Lead Python (Full Stack) /AI Developer

Location: Phoenix, AZ - 3 days/week onsite

Position: Contract-W2/1099

Duration: Long Term - 24 - 36 months

Job Description

Lead Software Engineer - Full Stack & Agentic AI

Position Summary

We are seeking a highly skilled and innovative Lead Software Engineer to drive the design, development, and delivery of next-generation intelligent applications powered by Agentic AI. This role combines deep expertise in full-stack software engineering with hands‑on experience building AI-powered systems, autonomous agents, Retrieval-Augmented Generation (RAG) architectures, and enterprise-scale AI solutions.

As a technical leader, you will define architecture, establish engineering standards, mentor development teams, and guide the implementation of AI-driven solutions that deliver measurable business value. You will work across the entire software development lifecycle, from requirements analysis and architecture design through implementation, deployment, and production support.

The ideal candidate possesses strong software engineering fundamentals, extensive experience with modern web technologies, and a proven track record designing and implementing Agentic AI platforms, intelligent workflows, and AI-enabled business solutions.

Required Qualifications

Experience

8+ years of professional software engineering experience.

3+ years leading technical teams or serving as a lead engineer.

2+ years designing and implementing Generative AI or Agentic AI solutions in enterprise environments.

Demonstrated experience delivering large-scale enterprise applications from inception through production.

Technical Skills

Programming Languages

Advanced Java (Spring Boot)

Front-End Technologies

Advanced Angular

Advanced React

TypeScript

Databases

SQL Server

Oracle Database

Experience with database design, performance tuning, and optimization

Agentic AI architecture and implementation

Prompt Engineering

Retrieval-Augmented Generation (RAG)

Semantic search

AI evaluation frameworks

Multi-agent orchestration

Azure, AWS, or Google Cloud

Docker

GitHub Actions / CI-CD pipelines

Infrastructure as Code

Event-driven architecture

API design and integration

Distributed systems

Preferred Qualifications

Experience building enterprise AI platforms and AI governance frameworks.

Experience with Microsoft Copilot Studio, Azure AI Foundry, LangChain, LangGraph, or similar agent frameworks.

Experience designing knowledge graphs and semantic data models.

Experience implementing AI observability, evaluation, and monitoring solutions.

Experience with modernization and legacy transformation initiatives.

Experience with GitHub Copilot, AI-assisted software development, and automated code generation workflows.

Exposure to machine learning operations (MLOps) and AI Operations (AIOps).