Senior AI​/Machine Learning Engineer

Job Title:

AI/ML Software Engineer Overview / Summary

The AI/ML Software Engineer will design and build software tools that incorporate AI/ML techniques to automate narrowly defined tasks, assist internal users, and improve external user interactions. This role involves developing solutions such as chatbots, RPA tools, knowledge retrieval systems, and AI-driven data processing applications within defined infrastructure and system constraints.

• Design and build software systems integrating AI/ML techniques to automate tasks and enhance user services
• Collaborate on system architecture, workflows, and agent design decisions
• Contribute to technical decision-making for data processing, retrieval strategies, and system integration
• Evaluate and apply appropriate techniques, including LLM and non-LLM approaches
• Develop testing and evaluation pipelines for AI/ML systems
• Create unit and integration tests for AI-enabled workflows and data pipelines
• Generate and use synthetic data for evaluation and benchmarking
• Improve system performance, including accuracy, latency, and cost efficiency
• Support deployment of AI/ML applications in hybrid cloud environments
• Work with containerized applications to ensure reliable deployment and updates
• Optimize systems for environments with limited computational resources
• Deliver production-grade systems aligned with requirements
• Document system designs, workflows, and technical decisions
• Stay current with AI/ML advancements and apply them within project constraints

• Bachelor of Science in Engineering, Computer Science, Data Science, Mathematics, or a related field

• At least 3 years of experience in data science, machine learning, or applied AI development
• At least 3 years of experience in software engineering, architecture, or web development

• Front-end development using React and/or Angular
• Message queuing and event streaming (Rabbit
  
  MQ or Kafka)
• Elasticsearch for search and analytics
• Microservices development using Spring Boot or similar Java frameworks
• Cloud platforms (AWS, Azure, or Google Cloud)
• Dev Ops tools, Git, CI/CD pipelines
• Event-driven architecture design
• Strong Java proficiency (core libraries, concurrency, JVM fundamentals)
• Prime Faces and JSF integration
• Software design patterns and architectural best practices
• Containerization and orchestration (Docker, Kubernetes)
• RESTful APIs and integration patterns
• Relational and No
  
  SQL databases (Postgre
  
  SQL, MySQL, Mongo
  
  DB, Cassandra)
• Monitoring and observability tools (Prometheus, Grafana, ELK stack)
• Security best practices

• Python proficiency for backend services, APIs, and data pipelines
• Experience with LLMs, embeddings, and RAG systems
• Fine-tuning language or embedding models
• Graph databases (e.g., Neo4j) and graph-based retrieval techniques
• AI system testing, evaluation pipelines, and synthetic data usage
• Validation of AI outputs and mitigation of hallucinations
• Experience with containerization, version control, and distributed systems
• Knowledge of NLP techniques (LLM and non-LLM approaches)