HITACHI ENERGY TECHNOLOGY SERVICES PRIVATE LIMITED
IT, Telecom & Internet
AppliedAIEngineer
“Applied AI Engineer at HITACHI ENERGY TECHNOLOGY SERVICES PRIVATE LIMITED. Skills: Applied AI, Machine Learning, Generative AI, LLMs, Python, Cloud Platforms (Azure), API/Microservice Development. evaluating GENAI for enterprise use cases. contributing to the development and implementation of agentic AI solutions”
What You'll Achieve.
enabling the CSS functions to deliver their services with greater efficiency and effectiveness; improve accuracy, reliability, and consistency across business scenarios; ensuring solutions meet required performance, scalability, reliability, and compliance standards
Industry & Context.
analytical and debugging skills to resolve issues across pipelines, model inference, and integrations
What They're Looking For.
Must Have
bachelor’s or master’s degree in computer science, Data Science, AI/ML, or a related technical field, 3–5 years of hands-on experience working on applied AI, machine learning, or AI solution delivery projects, Practical experience with Python and commonly used ML/NLP libraries in delivery environments, Exposure to LLMs, transformer models, embeddings, and enterprise generative AI platforms, Experience with Microsoft Azure, including services such as Azure OpenAI, Azure ML, Azure Functions, Azure App Service, Azure Kubernetes Service (AKS), Azure DevOps, or related cloud components used in solution delivery, Experience using Docker/Kubernetes or Azure serverless frameworks for packaging and deploying AI services, Ability to develop, test, and deploy APIs or microservices that integrate AI capabilities with business applications and automation platforms, Proficiency in both spoken & written English language is required
Nice to Have
Knowledge of the Model Context Protocol (MCP)
What You'll Do.
evaluating GENAI for enterprise use cases
contributing to the development and implementation of agentic AI solutions
performing basic hallucination checks and output validation
monitoring model performance
and inference quality
supporting periodic tuning cycles
and maintaining effective prompts
creating reusable prompt templates
and structured prompt patterns
understanding requirements and delivering AI powered solutions
and deploying APIs or microservices
developing AI solution components using Python or any programming language
and well documented code
participating in code reviews
technical discussions
and sprint-level engineering activities
following best practices for testing
and AI model lifecycle management
ensuring compliance with applicable external and internal regulations
How You'll Work.
Team & Collaboration
work closely with automation developers and business teams; contribute to solution architecture discussions; work with automation teams, developers, and business stakeholders; caring for your colleagues and the business
Communication Scope
Effective communication and collaboration skills
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