AI / Java Architect

AI - Java Architect

Full time only

Atlanta, GA

Description:

• We are seeking an experienced Developer III with strong solution engineering expertise to deliver scalable, cloud-native data and AI-driven solutions. This role requires hands-on ownership across the full software development lifecycle (analysis, design, development, and testing), with a clear expectation that testing and quality engineering are core and mandatory responsibilities.
• The ideal candidate will bring deep expertise in Java/ Python, AWS services (Redshift, RDS, GLUE, DMS, ECS, Bedrock), and Generative AI, with a strong ability to design and implement robust, production-ready systems. Experience with Apache Spark and GraphQL APIs is a strong plus.
• Key Responsibilities
• Solution Engineering & Analysis (Required)
• Lead requirements analysis by collaborating with business stakeholders, product managers, and technical teams
• Translate business needs into end-to-end scalable architecture and solution designs
• Design cloud-native systems leveraging AWS services (Redshift, RDS, DMS, ECS, Bedrock)
• Evaluate solution trade-offs around performance, scalability, cost, and maintainability
• Produce detailed technical specifications, architecture diagrams, and design documentation
• Development (Required)
• Design, develop, and maintain backend services and applications using:
• Java (Spring Boot, microservices)
• Python (APIs, data processing, GenAI integration)
• Build and optimize data pipelines and data access layers using Redshift and RDS
• Develop event-driven and containerized applications using ECS
• Develop GenAI-enabled applications using AWS Bedrock, including LLM-based workflows and RAG patterns
• Testing & Quality Engineering (Mandatory Core Responsibility)
• Own testing as an integral part of development—not a separate function
• Design and implement comprehensive test strategies, including:
• Unit testing, Integration testing, End-to-end/system testing, Regression testing
• Build and maintain automated test frameworks and integrate with CI/CD pipelines
• Validate: Data accuracy across Redshift/RDS pipelines, Performance and scalability of services
• Reliability and correctness of GenAI outputs
• Actively debug, troubleshoot, and resolve defects, ensuring production-grade quality
• Data Engineering & Processing
• Design and manage structured and semi-structured data workflows in Redshift and RDS
• Implement efficient data ingestion and transformation strategies
• (Preferred) Develop large-scale distributed data processing using Apache Spark (PySpark/Scala)
• GenAI & AI Integration
• Build and deploy applications leveraging Generative AI (LLMs via AWS Bedrock)
• Implement: Prompt engineering strategies
• Retrieval-Augmented Generation (RAG) architectures
• Agentic workflows
• Ensure responsible AI practices including performance tuning, monitoring, and governance
• Collaboration & Delivery
• Work in a fast-paced Agile environment, contributing to sprint planning and reviews
• Collaborate across engineering, data, and product teams
• Provide technical leadership and mentorship where needed
• Support production deployments and ongoing system enhancements
• Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
• 5+ years of experience in software engineering and solution design
• Strong expertise in:
• Java (Spring Boot, microservices architecture), Python (data engineering, APIs, AI/ML integration)
• Hands-on experience with AWS services, including:
• Amazon Redshift
• Amazon RDS
• AWS DMS (Database Migration Service)
• Amazon ECS (containerized workloads)
• Amazon Bedrock (GenAI services)
• Proven experience owning end-to-end SDLC (analysis, development, testing)
• Strong understanding of distributed systems and cloud-native architectures
• Preferred Qualifications: Experience with Apache Spark (PySpark or Scala Spark)
• Experience designing and implementing GraphQL APIs
• Knowledge of CI/CD pipelines, DevOps practices, and containerization (Docker/Kubernetes)
• Experience with vector databases and GenAI ecosystem tools
• Key Skills: Strong solution engineering and system design capabilities, Ability to independently own analysis → development → testing lifecycle, Strong focus on quality engineering and test-driven development (TDD)
• Excellent problem-solving, debugging, and performance optimization skills
• Strong communication and stakeholder collaboration