Java AI Engineer: Agentic AI, LLMs & Microservices

Mindera; United States; Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

Health Insurance

Flexible working hours

Open holidays

Profit distribution for everyone

Mindera Annual Trip

Training & conferences

Child Care vouchers

Job summary

Mindera is seeking a Java AI Enabled Engineer to design, build, and maintain scalable microservices using Java 17/21+ and Spring Boot. You will architect autonomous AI agents with memory management and integrate Azure Co-pilot via robust REST APIs.

You will craft prompts, ensure safe model outputs, and implement guardrails with observability for enterprise-grade reliability. Collaboration with app engineers, PMs, data, and frontend teams will shape end-to-end mobile experiences.

Qualifications

• Bachelor's degree in CS, Engineering, or related field.
• 7+ years of professional experience.
• Proven Java Developer with Spring Boot experience.
• Experience with agentic AI and LLMs.
• Knowledge of LangChain or similar orchestration frameworks.
• Strong written API/architecture documentation skills.

Responsibilities

• Design, build, and maintain scalable microservices in Java 17+/Spring Boot.
• Architect autonomous AI agents and memory management.
• Integrate Azure Co-pilot into enterprise apps via REST APIs.
• Craft and version-control prompts for safe model outputs.
• Implement guardrails, observability, and reliability for AI features.
• Collaborate with App Engineers, PMs, data and frontend teams to deliver end-to-end mobile experiences.

Skills

Backend Architecture

Java Developer

Spring Boot

Agentic AI / LLMs

System Design

Education

Bachelor’s degree in CS/Engineering

Tools

LangChain

Spring Boot

Azure AI Services

Job description

Mindera is seeking a Java AI Enabled Engineer to design, build, and maintain scalable microservices using Java 17/21+ and Spring Boot. You will architect autonomous AI agents with memory management and integrate Azure Co-pilot via robust REST APIs.

You will craft prompts, ensure safe model outputs, and implement guardrails with observability for enterprise-grade reliability. Collaboration with app engineers, PMs, data, and frontend teams will shape end-to-end mobile experiences.