Description

Key Responsibilities:

• Design and develop scalable backend applications and services using Java and Spring Boot.
• Build event-driven and distributed services using Kafka, REST APIs, and microservices architecture.
• Integrate NLP, machine learning, and LLM capabilities into Java-based enterprise applications.
• Build or integrate NLP solutions for text classification, clustering, intent detection, and related use cases.
• Perform data analysis and data validation using SQL.
• Design and deploy LLM workflows involving prompt engineering, evaluation, and Retrieval-Augmented Generation (RAG).
• Develop integrations between Java applications and Python-based AI/ML or model-serving services when appropriate.
• Contribute to agentic AI workflows supporting multistep interactions, tool execution, validation, and workflow orchestration.
• Apply production engineering practices covering scalability, resiliency, security, testing, monitoring, and performance optimization.
• Contribute to LLMOps and MLOps practices, including evaluation, monitoring, versioning, deployment, and lifecycle management.
• Collaborate with AI/ML, product, platform, data, and DevOps teams.
• Participate in architecture reviews, code reviews, technical planning, and production support.
• Mentor junior and offshore engineers and promote engineering best practices.

Requirements:

• 10 years of total technology or software-engineering experience.
• Strong hands-on backend development experience using Java.
• Strong experience with Spring Boot, REST APIs, and microservices.
• Experience with Kafka or comparable event-driven messaging technologies.
• Practical experience implementing or integrating AI/ML capabilities in production applications.
• Experience with NLP use cases such as text classification or clustering.
• Experience integrating machine learning models, NLP services, or LLM-based capabilities with enterprise applications.
• Hands-on experience with LLM concepts and solutions, including:
• Prompt engineering
• LLM evaluation
• Retrieval-Augmented Generation
• Strong SQL and relational-database experience.
• Experience with software testing, CI/CD, security, monitoring, and production support.
• Strong communication and cross-functional collaboration skills.

Preferred Qualifications:

• Experience with agentic AI or multi-agent orchestration.
• Experience with LLMOps or MLOps in production environments.
• Cloud experience with AWS, Azure, or Google Cloud Platform.
• Experience with Docker and Kubernetes.
• Experience integrating Java services with Python-based AI/ML components.
• Experience with vector databases and semantic search.
• Familiarity with voice AI, IVR, conversational AI, intent detection, or call-routing systems. Voice and IVR experience are preferred but not required.
• Experience mentoring distributed, offshore, or junior engineering teams

Key Skills

Education

Bachelor’s degree