AI Engineer / AI Platform Engineer

Acunor; San Diego (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Acunor in San Diego is seeking an experienced AI Engineer / AI Platform Engineer to design, build, and integrate enterprise AI solutions that boost software engineering productivity and automation.

Ideal candidates have a strong software engineering background and hands-on experience with GenAI, AI agents, LLM-based applications, AI-assisted development tools, and modern enterprise architecture. You will help shape AI-enabled SDLC and scalable backend services.

Qualifications

• 8+ years of software engineering, full stack development, or platform engineering experience.
• Hands-on experience with GenAI, LLM applications, AI agents, RAG, or intelligent automation.
• Experience using AI-assisted development tools such as Cursor, Claude Code, GitHub Copilot, or similar.
• Strong experience with APIs, microservices, cloud-native architecture, Agile, DevOps, and CI/CD.

Responsibilities

• Design and build AI-enabled applications and services for enterprise use.
• Integrate AI solutions with internal applications and data sources.
• Develop reusable AI components, accelerators, and tooling for enterprise adoption.

Skills

Software engineering

Full stack development

Platform engineering

Generative AI

LLM applications

AI agents

APIs & microservices

CI/CD

Agile / DevOps

Communication

Tools

Cursor

Claude Code

GitHub Copilot

ChatGPT Enterprise

Job description

Experience: 8+ years preferred

Role Overview

We are looking for a hands-on AI Engineer / AI Platform Engineer to design, build, and integrate enterprise AI solutions that improve software engineering productivity, automation, and intelligent decision-making.

This role is ideal for someone with strong software engineering experience and practical exposure to Generative AI, AI agents, LLM-based applications, AI-assisted development tools, and modern enterprise application architecture.

Key Responsibilities

• Build AI-enabled applications using LLMs, AI agents, RAG, enterprise search, intelligent assistants, and workflow automation.
• Develop reusable AI services, APIs, accelerators, and components for enterprise adoption.
• Integrate AI solutions with internal applications, enterprise data sources, APIs, and workflow platforms.

AI-Enabled SDLC Implementation

• Apply tools such as Cursor, Claude Code, GitHub Copilot, ChatGPT Enterprise, or similar platforms across the SDLC.
• Support use cases across requirements, design, coding, debugging, testing, documentation, and deployment.
• Work with internal AI teams to refine AI engineering workflows, prompting patterns, and reusable development frameworks.

Application Engineering & Platform Readiness

• Design and develop backend services, APIs, microservices, and frontend components as needed.
• Support Agile delivery, CI/CD integration, rapid prototyping, stakeholder demos, and production readiness.

Required Qualifications

• 8+ years of software engineering, full stack development, or platform engineering experience.
• Hands-on experience with GenAI, LLM applications, AI agents, RAG, or intelligent automation.
• Experience using AI-assisted development tools such as Cursor, Claude Code, GitHub Copilot, or similar.
• Strong experience with APIs, microservices, cloud-native architecture, Agile, DevOps, and CI/CD.
• Exposure to LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, or Google Gemini is preferred.
• Strong communication skills and ability to work with product, engineering, architecture, and business teams.

Ideal Candidate Profile

The ideal candidate is not just a traditional full stack developer. This person should be able to build working AI solutions, apply AI tools in delivery, integrate AI into enterprise systems, and support AI-enabled SDLC adoption.