Senior AI/LLM Engineer
Ntt Data
- Location
- US
- Workplace
- Remote
- Employment
- Full Time
- Salary
- USD 55–62/hr
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.
Responsibilities
- Design, develop, and deploy enterprise-scale Generative AI applications using modern LLM technologies
- Build production-grade backend services using Python and modern software engineering practices
- 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 capabilities
- Develop intelligent multi-agent AI systems capable of orchestrating complex business workflows
- Design AI solution architectures that are scalable, secure, maintainable, and aligned with enterprise standards
- 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
- Evaluate LLM performance and implement techniques to improve response quality
- Establish AI governance, model evaluation, and responsible AI best practices
- Monitor AI application performance and continuously optimize latency, cost, and quality
- Build cloud-native AI solutions using Azure or AWS AI services
- Implement Azure AI Search and vector search capabilities
- Design secure enterprise AI applications following cloud security and governance standards
- Collaborate with DevOps teams to deploy AI solutions using CI/CD pipelines
- Partner with business stakeholders to understand AI use cases and translate them into scalable technical solutions
- Present architecture decisions, solution approaches, and AI strategies to both technical and non-technical audiences
- Mentor junior engineers and contribute to AI engineering best practices across the organization
Requirements
- 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 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 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
- Strong understanding of scalable enterprise application architecture
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field
Preferred
- 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
- Experience optimizing LLM inference performance and AI operational costs
Skills
- Python
- JavaScript
- Generative AI
- Large Language Models (LLMs)
- OpenAI
- Anthropic Claude
- Gemini
- Llama
- Retrieval-Augmented Generation (RAG)
- Multi-Agent AI Orchestration
- LangChain
- Langfuse
- AI Solution Architecture
- Azure AI Search
- Vector Databases
- Prompt Engineering
- REST APIs
- Microservices
- Event-Driven Architecture
- Azure
- AWS
- LangGraph
- AutoGen
- CrewAI
- Semantic Kernel
- Pinecone
- Weaviate
- ChromaDB
- Qdrant
- Milvus
- Docker
- Kubernetes
- CI/CD
- MLOps