AI Engineer

Dimensionless Technologies; Índia; Presencial; INR 900 000 - 1 500 000; Tempo integral

Resumo da oferta

Dimensionless Technologies seeks a GenAI/LLM engineer to design and deploy advanced AI applications using LangChain, LlamaIndex, and Semantic Kernel. You will optimize models, build RAG pipelines, and containerize services with FastAPI and Azure Functions to ensure high availability and low latency.

Collaborate with Product, DevOps, and Data teams to move high-impact use cases from POC to production, track model performance, address hallucination and context-window issues, and uphold ethical AI

Qualificações

• 4-7 years of professional software engineering experience.
• 2 years of GenAI/LLM production experience.
• Deep proficiency in Python and asynchronous programming.
• Experience with commercial APIs (OpenAI GPT-4o, Azure OpenAI) and open-source models.

Responsabilidades

• Design and deploy LLM-based applications using LangChain, LlamaIndex, or Semantic Kernel.
• Lead model optimization and fine-tuning for performance, latency, and cost-efficiency.
• Architect and optimize Retrieval-Augmented Generation (RAG) pipelines with vector databases.
• Containerize services with Docker and deploy via FastAPI, Azure Functions, and CI/CD pipelines.

Conhecimentos

Python

Async programming

Typing standards

Clean code

GenAI/LLM experience

OpenAI APIs

Ferramentas

FastAPI

Docker

Git

CI/CD

Descrição da oferta de emprego

• LLM Orchestration: Design and deploy sophisticated LLM-based applications using frameworks such as LangChain, LlamaIndex, or Semantic Kernel.
• Model Optimization: Lead the fine-tuning of open-source and proprietary models to improve performance, latency, and cost-efficiency.
• Advanced RAG Systems: Architect and optimize Retrieval-Augmented Generation (RAG) pipelines utilizing vector databases like Pinecone, FAISS, Weaviate, or Azure AI Search.
• Scalable Deployment: Containerize services using Docker and deploy via FastAPI and Azure Functions to ensure high availability and low latency.
• Productization: Build and scale enterprise-grade chatbots, copilots, and automated content generation tools using OpenAI/Azure OpenAI and Hugging Face.
• Prompt Engineering: Implement and manage advanced prompt optimization and versioning workflows to enhance model accuracy. track model performance, hallucination rates, and drift in production.
• Operationalization: Collaborate with cross-functional teams (Product, DevOps, Data) to identify high-impact use cases and move them from POC to production.
• Best Practices: Set the standard for GenAI engineering, including model selection criteria, performance tracking, and ethical AI safeguards.

Required Skills & Qualifications

• Overall Experience: 4-7 years of professional software engineering experience.
• GenAI Domain Experience: 2 years of dedicated, hands-on experience building GenAI, LLM, and OCR solutions in production environments.
• Programming Mastery: Deep proficiency in Python with expertise in asynchronous programming, typing standards, and clean code principles.
• Generative AI & LLMs: Hands-on experience with commercial APIs (OpenAI GPT-4o, Anthropic Claude, Azure OpenAI) and open-source models (Llama 3, Mistral), along with modern agentic frameworks.
• Vector Infrastructure & Search: Practical experience with hybrid search (dense + sparse), re-ranking algorithms, metadata filtering, and vector index tuning.
• Backend & Cloud: Strong background in FastAPI, Docker, Git, CI/CD pipelines, and
• Problem Solving: Proven track record of solving hallucination, context window limitations, and data grounding issues in production.