Java AI Engineer

Divit Technologies, Inc.

United States

7 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Microsoft Azure Cloud Engineering Databases Continuous Integration DevOps Distributed Systems Fault Tolerance Python (Programming Language)

+35 more

PostgreSQL Machine Learning MongoDB MySQL NoSQL RabbitMQ Redis Tensorflow Prometheus Software Engineering Data Streaming Systems Integration Scripting Google Cloud Enterprise Software Applications Spring Cloud Pytorch Istio Large Language Models Grafana Spring-boot Caching Generative AI Backend Event Driven Architecture Containerization Cassandra Apache Kafka Graphql Machine Learning Operations Api Design Api Gateway Dynatrace Docker Microservices

Requirements

10+ years of overall software engineering experience, with a significant focus on Java and microservices architecture.

Strong hands-on experience with Java, Spring Boot, Spring Cloud, and related frameworks for building microservices.
Solid working experience in Python - scripting, automation, backend services, or AI/ML-adjacent development.
Exposure to AI/ML concepts and tools - e.g., integrating LLMs, AI-powered features, model APIs, or ML pipelines into applications.
Proven experience as a Technical Lead or Architect, with a track record of leading and mentoring engineering teams.
Strong understanding of distributed systems concepts - scalability, fault tolerance, caching, messaging (Kafka/RabbitMQ), and eventual consistency.
Experience with containerization and orchestration - Docker and Kubernetes.
Proficiency with cloud platforms (AWS, Azure, or Google Cloud Platform) and cloud-native architecture patterns.
Strong grasp of API design (REST/GraphQL), API gateways, and service mesh concepts.
Experience with CI/CD pipelines, DevOps practices, and infrastructure-as-code.
Solid understanding of databases - both relational (PostgreSQL/MySQL) and NoSQL (MongoDB, Cassandra, Redis).
Excellent communication skills with the ability to advise stakeholders and align technical strategy with business objectives.
Strong problem-solving skills with the ability to troubleshoot complex, production-grade distributed systems. Preferred / Good to Have:
Experience building or integrating Generative AI / LLM-based features into enterprise applications.
Familiarity with AI/ML frameworks such as TensorFlow, PyTorch, LangChain, or similar.
Prior experience in a formal Solution Architect or Enterprise Architect role.
Knowledge of event-driven architecture and streaming platforms (Kafka, Kinesis).
Experience with observability tools - Prometheus, Grafana, ELK/EFK stack, distributed tracing.
Relevant certifications - AWS/Azure/Google Cloud Platform Solutions Architect, or Java/Spring certifications.
Experience working in Agile/Scrum environments and leading sprint-level technical planning. What You Will Bring:
A strategic mindset with the ability to balance technical depth and business pragmatism.
Strong ownership and accountability for technical outcomes and team delivery.
Leadership presence to advise, influence, and align cross-functional and senior stakeholders.
A continuous-learning mindset, staying current with emerging technologies including AI/ML advancements.