Senior Java Software Engineer
Role: Full Stack Java Developer Location: Rockville, MD ((3 days onsite & 2 days remote)) Must have Generative AI experience!!! Job Description: Key Responsibilities· Full Stack Development: Design, develop, and maintain scalable full-stack applications with Angular frontends and microservices-based backends, ensuring seamless integration and optimal performance· API & Microservices Architecture: Build and optimize RESTful and GraphQL APIs, design microservices architectures, and implement efficient inter-service communication patterns· Generative AI Integration: Architect and implement Generative AI solutions including LLM integration, prompt engineering, RAG (Retrieval-Augmented Generation) pipelines, and AI-powered features into production applications· Cloud Infrastructure: Design and deploy cloud-native solutions on AWS, leveraging serverless architectures, containerization, and managed services for scalability and reliability· Database Design & Optimization: Implement efficient database schemas, optimize queries, and manage both SQL and NoSQL databases to support application requirements· Technical Leadership: Provide technical guidance and mentorship to team members, lead code reviews, establish best practices, and drive architectural decisions· AI/ML Model Integration: Collaborate with data science teams to integrate ML models, implement model serving infrastructure, and ensure responsible AI practices including bias monitoring and explainability· Performance & Quality: Ensure applications meet performance benchmarks, implement comprehensive testing strategies, and maintain high code quality standards Required Qualifications· Bachelor's degree in computer science, Software Engineering, or related field (Master's preferred)· 7+ years of software engineering experience with full-stack development· Frontend Expertise: 3+ years of production experience with Angular (latest versions), TypeScript, RxJS, NgRx/state management, and responsive UI design· Backend Expertise: Strong proficiency in Java and/or Python for API and microservices development· API Development: Proven experience designing and implementing RESTful APIs and/or GraphQL services· Cloud & DevOps: Hands-on experience with AWS services (Lambda, ECS/EKS, API Gateway, S3, RDS, DynamoDB, etc.) and containerization (Docker, Kubernetes)· Database Proficiency: Experience with both relational (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB) databases· Generative AI Experience: 1+ years working with LLMs (OpenAI, Anthropic, AWS Bedrock), prompt engineering, vector databases, and embedding models Preferred Qualifications· Experience with LangChain, LlamaIndex, or similar LLM orchestration frameworks· Background implementing RAG architectures with vector databases (Pinecone, Weaviate, pgvector, OpenSearch)· Knowledge of fine-tuning techniques, model evaluation, and AI safety practices· Experience with real-time data processing and streaming architectures (Kafka, Kinesis)· Familiarity with event-driven architectures and asynchronous messaging patterns· Understanding of security and compliance requirements in regulated financial environments· Experience with microservices patterns (circuit breakers, service mesh, distributed tracing)· Contributions to open-source projects or technical publications in AI/ML domains Skills & Competencies· Full Stack Mastery: End-to-end ownership of features from UI to database, with deep understanding of frontend-backend integration patterns· Architectural Thinking: Ability to design scalable, maintainable architectures that balance business needs, technical constraints, and future growth· AI/ML Integration: Practical knowledge of integrating Generative AI capabilities into production systems, including handling latency, costs, and reliability challenges· Technical Problem-Solving: Strong debugging and troubleshooting skills across the full technology stack, including AI model behavior and performance issues· Collaboration & Communication: Excellent ability to work with cross-functional teams, translate business requirements into technical solutions, and communicate complex concepts clearly· Pseudo-Lead Capabilities: Self-motivated to drive initiatives, mentor peers, facilitate technical discussions, and influence technical direction without formal management responsibilities· Quality & Testing Focus: Strong commitment to automated testing (unit, integration, e2e), code quality, and continuous improvement· Learning Agility: Rapid adoption of new technologies and frameworks, particularly in the fast-evolving AI/ML landscape Key Technologies:· Frontend: Angular (16+), TypeScript, RxJS, NgRx, HTML5/CSS3, JavaScript· Backend: Java (Spring Boot), Python (FastAPI, Flask), Node.js· APIs: RESTful services, GraphQL (Apollo), gRPC· Generative AI: AWS Bedrock, OpenAI API, LangChain, vector databases, embedding models, prompt engineering frameworks· Databases: PostgreSQL, MongoDB, DocumentDB, DynamoDB, Redis, Vector databases (pgvector, OpenSearch)· Cloud Platform: AWS (Lambda, ECS/EKS, API Gateway, S3, RDS, DynamoDB, Bedrock, SageMaker, CloudWatch)· Microservices & Integration: Docker, Kubernetes, service mesh, API Gateway, message queues (SQS, SNS, Kafka)· DevOps & CI/CD: GitLab CI/CD, Jenkins, Terraform, CloudFormation, monitoring and observability tools· Testing: Jest, Jasmine, Karma, JUnit, PyTest, Selenium, Cypress