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Senior AI/LLM Engineer – Generative AI Solutions

VDart, Inc.United States🇺🇸United StatesPosted 29 Jul 2026

Quick Overview

Work Type
Remote
Level
Mid Senior

Job Description

Job Title: Senior AI/LLM Engineer – Generative AI Solutions

Location: Remote

Type: Contract

Project Overview

  • We are seeking an experienced Senior AI/LLM Engineer to design, develop, and deploy enterprise-grade Generative AI solutions that leverage Large Language Models (LLMs) to solve complex business challenges. The ideal candidate will have strong expertise in Python development, Retrieval-Augmented Generation (RAG), AI orchestration frameworks, and cloud-native AI architectures.
  • This role will work closely with product owners, solution architects, data engineers, and business stakeholders to build scalable, secure, and production-ready AI applications powered by OpenAI and other leading foundation models.

Key Responsibilities

AI Solution Design & Development

  • 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.
  • AI Architecture & Integration
  • 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.
  • Prompt Engineering & Model Optimization
  • 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.
  • Cloud & Enterprise AI
  • 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.
  • Stakeholder Collaboration
  • 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.

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field.
  • 6+ years of software engineering or machine learning engineering experience.
  • Minimum 3+ years of hands-on experience building Artificial Intelligence 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 (preferred), 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.
  • Strong understanding of scalable enterprise application architecture.
  • Excellent analytical, problem-solving, and communication skills.

Required Technical Skills

  • Python
  • JavaScript
  • Generative AI
  • Large Language Models (LLMs)
  • OpenAI (Preferred)
  • 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 or AWS Cloud Services
  • Preferred Qualifications
  • 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.

Nice to Have

  • 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

Docker
Microservices
AWS
MLOps
Machine Learning
Scrum
Agile
Azure
Compliance
Generative AI
JavaScript
Kubernetes
LLM
Python
REST

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