Senior Java GenAI Architect | Microservices & AI Systems

Photon

Dallas (TX)

On-site

USD 140,000 - 180,000

Full time

2 days ago

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Job summary

Photon in Dallas is seeking an experienced Java Developer to design scalable, high-performance enterprise applications and integrate GenAI capabilities into distributed systems. You will lead system design efforts and work across product, data, and ML teams.

The ideal candidate has 8+ years of Java/J2EE experience, strong Kafka and cloud skills, and hands-on GenAI/LLM integrations. This role offers growth in a fast-paced digital modernization environment with modern tech.

Qualifications

8+ years of Java/J2EE application development experience.
Expertise in Java, Spring Boot and microservices architecture.
Strong understanding of system design, distributed systems, and API architecture.
Hands-on experience with Apache Kafka and event-driven architecture.
Strong Python programming for AI/GenAI integrations.
Experience designing or implementing GenAI architectures and LLM-based applications.
Knowledge of RAG, vector databases, embeddings, and prompt engineering.
Experience integrating LLMs such as OpenAI, Gemini, Claude, Llama, or similar models.
Strong REST API security, scalability, and performance optimization.
Experience with cloud platforms (AWS, Azure, GCP) and DevOps practices.

Responsibilities

Design and develop scalable, resilient applications using Java, Spring Boot, and Microservices.
Own and contribute to high-level and low-level system design, architecture, and technical solutioning.
Design event-driven architectures using Apache Kafka for real-time data and asynchronous processing.
Develop secure and scalable REST APIs and backend services.
Design and implement GenAI/LLM-based architectures, including RAG, AI agents, model integration, and AI-powered enterprise solutions.
Work with Python for AI/ML integrations, automation, data processing, and GenAI application development.
Integrate LLMs and AI services with existing Java-based enterprise applications and microservices.
Evaluate and recommend appropriate technologies, frameworks, design patterns, and architectural approaches.
Drive performance, scalability, reliability, security, and observability across distributed systems.
Collaborate with product managers, architects, data engineers, ML engineers, and development teams.
Provide technical leadership, conduct code/design reviews, and mentor engineering teams.