What are the responsibilities and job description for the Senior AI Engineer (Java) position at ITTConnect?
ITTConnect is seeking an experienced Senior AI Engineer (JAVA) to work for a client that is a global leader in consulting, digital transformation, technology and engineering services present in nearly 50 countries. End client is in the telecom industry.
We are seeking a highly experienced senior AI Engineer, designing scalable LLM and NLP solutions for high-volume customer interactions. This role will drive architecture, best practices, and innovation across voice AI systems.
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.