Java Engineer with AI

Key Responsibilities

Design, build, and maintain scalable full-stack solutions, integrating sophisticated AI models and advanced data retrieval mechanisms into intuitive, scalable, and responsive applications. Applications integrating Retrieval-Augmented Generation (RAG)-based AI solutions.

Develop responsive, intuitive user interfaces leveraging modern JavaScript frameworks (React, Angular Design, build, and maintain AI-driven full-stack applications leveraging Retrieval-Augmented Generation (RAG, Vue) to deliver seamless AI-driven user experiences.

Build robust backend APIs and microservices that interface with AI models,) and related AI technologies vector databases, and retrieval engines.

Integrate Large Language Models (LLMs), embeddings, vector databases, and search algorithms.

Collaborate closely with AI/ML specialists, product owners, and UX designers to translate complex AI capabilities into user-friendly interfaces.

Implement robust into applications.

Collaborate closely with data scientists, machine learning engineers, and product teams to define APIs and backend services to requirements, optimize AI integration, and deliver innovative features support RAG model integrations and real-time data retrieval.

Develop responsive front-end interfaces utilizing modern frameworks.

Create and manage RESTful and GraphQL APIs to facilitate efficient, secure data exchange between frontend (React, Angular, Vue) that seamlessly interact with AI backend services.

Ensure robust security measures, scalability, and performance components, backend services, and AI engines.

Participate actively in code reviews, architecture decisions, and Agile ceremonies, ensuring best practices in software engineering and optimization of AI-integrated applications.

Participate actively in code reviews, technical design discussions, and agile ceremonies.

Continuously AI integration.

Troubleshoot, debug, and enhance performance of both frontend and backend systems, focusing on AI latency, accuracy explore emerging AI trends and technologies, proactively recommending improvements, and scalability.

to enhance product capabilities.

Qualifications

Bachelors degree in computer science, Engineering, or a related technical discipline.

3+ years of experience in full-stack software engineering, with demonstrated, Engineering, or related discipline.

Minimum of 3+ years of experience in full-stack software development.

Proficiency experience integrating AI/ML services.

Strong proficiency in front-end technologies including HTML, CSS, JavaScript, and frameworks such as React, Angular, or

in frontend technologies (HTML, CSS, JavaScript Backend development expertise with Node, React, Angular, Vue).

Strong , Python, Java, or .NET, particularly experience building RESTful APIs and in , Python, Java, or .NET.

Hands-on experience integrating AI/ML models, particularly NLP- Experience integrating AI and NLP models, including familiarity with Retrieval-Augmented Generation (RAG), OpenAI APIs, LangChain, or similar frameworks.

Proficiency with relational-based Large Language Models (e.g., GPT, BERT, LLaMA).

Familiarity with RAG architectures, vector databases (e.g., Pinecone, We and NoSQL databases (PostgreSQL, MongoDB, etc.) and familiarity with vector databases (aviate, Milvus), and embedding techniques.

Experience with RESTful APIs, GraphQL, microservices, and cloud-native architecture (AWS, Azure, GCP).

e.g., Pinecone, Chroma, Weaviate) is a plus.

Solid understanding- Solid understanding of databases (SQL/NoSQL) and data modeling best practices.

Experience with version control systems (Git), CI/CD pipelines, and containerization (Docker of version control (Git) and CI/CD pipelines.