Senior AI/LLM Engineer

Ntt Data

Posted 1mo ago

The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.

Design, develop, and deploy enterprise-scale Generative AI applications using modern LLM technologies
Build production-grade backend services using Python
Develop scalable AI architectures utilizing OpenAI, Anthropic Claude, Gemini, Llama, or similar foundation models
Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and semantic search
Develop intelligent multi-agent AI systems for complex business workflows
Integrate AI capabilities into existing enterprise applications, APIs, and business workflows
Develop and consume REST APIs, microservices, and event-driven services for AI applications
Implement AI orchestration frameworks such as LangChain and related agent frameworks
Develop and optimize prompts for improved accuracy, reasoning, and business outcomes
Establish AI governance, model evaluation, and responsible AI best practices
Build cloud-native AI solutions using Azure or AWS AI services
Collaborate with DevOps teams to deploy AI solutions using CI/CD pipelines
Mentor junior engineers and contribute to AI engineering best practices

6+ years of software engineering or machine learning engineering experience
Minimum 3+ years of hands-on experience building AI and Generative AI solutions
3 to 5 years of strong hands-on experience developing production applications using Python
1 to 3 years of experience building applications using OpenAI, Anthropic Claude, Gemini, Llama, or similar LLM platforms
3+ years of strong experience implementing Retrieval-Augmented Generation (RAG) architectures
1 to 3 years of experience integrating vector databases and semantic search solutions
1 to 3 years of strong understanding of LangChain and AI orchestration frameworks
Experience designing multi-agent AI architectures
Strong knowledge of prompt engineering, model evaluation, AI governance, and Responsible AI principles
Experience building REST APIs, microservices, and event-driven architectures
Experience with Azure or AWS cloud platforms
Bachelor's or Master's degree in Computer Science, AI, Software Engineering, or related field

Experience with LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar AI agent frameworks
Experience with vector databases such as Pinecone, Weaviate, ChromaDB, Qdrant, Milvus, or Azure AI Search
Experience with containerization technologies such as Docker and Kubernetes
Knowledge of CI/CD pipelines and MLOps practices
Experience with AI observability and monitoring platforms
Familiarity with enterprise security, compliance, and Responsible AI frameworks
Experience working in Agile/Scrum environments
Experience developing enterprise copilots or AI assistants
Experience integrating AI into enterprise SaaS platforms
Knowledge of AI governance, security, and compliance standards

Skills