Job Title : Full Stack AI Engineer - Remote
We will conduct an IDV check ; make sure candidates are ready
Job has reopened. Google experience is required!
engineers with 10+ years of experience and strong Full Stack expertise, including Python/Go, React/Angular, DevOps, and agent development experience (ADK, A2A, MCP whith any LLMs). They should also have design and architecture experience, excellent communication skills, prior experience working on Google, and knowledge of the G3 Stack (BOQ, BOQ WEB/. Wiz, GRPC, Protocol buffer, etc.).
Google experience is required!
• What are "must-have” skills for this role:
1. BOQ 2. BOQ Web 3. Wiz
• Years of experience required for each skill: 10+ years (or as much as is possible given some of these are new)
• What are some "nice-to-have” skills:
1. Python 2. React 3. DevOps
engineers with 10+ years of experience and strong Full Stack expertise, including Python/Go, React/Angular, DevOps, and agent development experience (ADK, A2A, MCP whith any LLMs). They should also have design and architecture experience, excellent communication skills, prior experience working on Google, and knowledge of the G3 Stack (BOQ, BOQ WEB/. Wiz, GRPC, Protocol buffer, etc.).
100% Remote, must be based in the US.
Key focus is G3 level expertise touching both frontend systems (BoQ Web & BoQ GOA) and backend infrastructure.
Work authorization: US Citizen (USC) or Green Card (GC) preferred; H1B is acceptable.
Requires proven hands-on work with AI agent frameworks and LLM integrations.
TOP HARD SKILLS
Full Stack Development (TSX, HTML/CSS, JS, Lit/Angular/Wiz) – 3+ years
Backend Services (Go, Python, Java Flume, SQL, TS BoQ) – 3+ years
LLM Interaction & AI Agent Architectures – 1+ years
NICE-TO-HAVES
Data visualization toolkits (Vega-Lite, Charts)
Enterprise scale infrastructure (Java Flume)
Prior client-specific architectural experience
DISQUALIFIERS
Non-US-based candidates.
Lack of core backend experience in Go, Python, or Java.
Purely traditional web developers with zero exposure to modern AI/LLM integration.
OVERVIEW
The G3 Full Stack AI Engineer will join an innovative team focused on building high-performance AI-driven web applications and scalable backend services. The role involves designing dynamic user interfaces, developing robust data processing and analytics pipelines, and integrating modern AI agent architectures and Large Language Model (LLM) interfaces.
DAY-TO-DAY RESPONSIBILITIES
Architect and implement front-end interfaces using modern web frameworks and technologies (HTML, CSS, JS, TSX, Lit, Angular, Wiz).
Build and maintain scalable backend microservices and databases utilizing Go, SQL, Python, Java Flume, and TS BoQ.
Design and implement data analytics and interactive visualizations to deliver clear user insights using tools like Vega-Lite and Charts.
Integrate Large Language Models (LLMs) and build autonomous AI agent architectures into existing system workflows.
Collaborate with cross-functional teams to engineer end-to-end applications supporting BoQ Web and BoQ GOA platforms.
Ensure high code quality, system performance, security, and scalability across all tier levels.
TOP 3 REQUIRED SKILLS
Full Stack Web Development (HTML/CSS/JS/TSX with Lit, Angular, or Wiz) – 3+ years
Backend Engineering (Go, Python, Java Flume, SQL) – 3+ years
AI Architectures & LLM Integration – 1+ years
ADDITIONAL DESIRED SKILLS
Data Visualization & Analytics (Vega-Lite, Charts)
Experience with TS BoQ and specialized web infrastructure
Knowledge of Google/Enterprise-grade software stack frameworks
IDEAL CANDIDATE PROFILE
The ideal candidate is a proactive, US-based Senior Full Stack Engineer with strong foundational backend and frontend capabilities complemented by practical experience in modern AI agent integration. They possess deep analytical problem-solving skills, work comfortably in distributed remote environments, and bring high adaptability to rapidly evolving AI technical stacks.
Job Responsibilities
Design, build, and maintain full-stack web applications and scalable back-end services.
Integrate Large Language Models (LLM) and develop AI agent-driven features into production environments.
Create interactive data visualisations and analytics dashboards to display complex insights clearly.
Collaborate with engineering teams to ensure optimal application performance, reliability, and security.