AI Java Engineer/Architect

AI Java Developer Lead who can design and implement enterprise-scale applications integrated with AI/GenAI capabilities, combining Java architecture + AI/ML expertise + cloud solutions., AI & Architecture:

Design end-to-end AI/GenAI architecture for enterprise applications

Build scalable AI systems including LLMs, ML/DL models, and neural networks

Define architecture patterns, standards, and best practices

Lead solution design discussions with stakeholders and clients

Java & Application Development:

Architect and develop Java-based enterprise applications (Spring Boot, Microservices)

Integrate AI models into Java applications (APIs, services, pipelines)

Ensure high performance, scalability, and security

Drive code quality, design patterns, and system optimization

Cloud & DevOps:

Design and deploy solutions on AWS / Azure / GCP

Implement CI/CD pipelines and containerization (Docker/K8s)

Ensure scalable and resilient distributed systems

Data & AI Engineering:

Design data pipelines, ingestion, transformation, and storage

Work with large datasets for AI model training and inference

Collaborate with data scientists and ML engineers

Ensure data quality, governance, and compliance

Core Java & Backend

Strong experience in Java, J2EE, Spring Boot, Microservices

Expertise in REST APIs, event-driven architecture

Knowledge of design patterns & system design

AI / ML Skills

Experience with:

Machine Learning / Deep Learning

LLMs & Generative AI (GPT, transformers)

Prompt Engineering

Hands-on with frameworks:

TensorFlow / PyTorch / Keras

Data & Big Data

Strong in SQL / NoSQL

Experience with data pipelines, ETL, Spark, Hadoop (optional)

Cloud & DevOps

AWS / Azure / GCP

Docker, Kubernetes

CI/CD tools (Jenkins, GitHub Actions)

Additional:

Frontend (optional): React / Angular

Strong understanding of security & compliance (enterprise systems)

Qualifications:

Bachelor's / Master's in Computer Science / AI / Data Science

10+ years in software development

3+ years in architecture roles

Experience in AI/ML-based enterprise solutions

Key Competencies

Strong system design & architecture mindset

Ability to handle large-scale distributed systems

Problem-solving and innovation in AI-driven solutions

Excellent communication & stakeholder management

Nice-to-Have:

Experience with GenAI use cases (chatbots, copilots, NLP systems)

Exposure to TOGAF / enterprise architecture frameworks

Knowledge of AI governance & ethical AI