5Data Inc
Website:
5datainc.com
Job details:
Company Description
5Data Inc. specializes in collecting, analyzing, processing, and tabulating data to provide actionable insights for businesses. By leveraging advanced analytics expertise, 5Data Inc. helps organizations make informed and forward-thinking decisions. With a focus on transforming raw data into meaningful insights, the company empowers businesses to navigate the challenges of a data-driven world effectively and strategically.
Hi ,
Please find the Job Description for the AI Engineer Role.
We request you to share the video recording as soon as possible. Please check the role specific questions and context below for video preparation.
LOCATION : REMOTE
SHIFT - NIGHT SHIFT ( PST Hours )
We are seeking a highly skilled and experienced AI/ML Developer to join our team. The ideal candidate will be a specialist in the rapidly evolving field of Large Language Models (LLMs) and generative AI, with a strong background in developing, integrating, and optimizing complex agentic and RAG-based systems.
Roles and Responsibility
LLM Integration & Development: Design, develop, and deploy production-grade applications leveraging various LLMs, context optimization, etc.
Agentic Workflows: Architect and implement sophisticated, multi-step and multi-agent workflows using frameworks like LangChain and LangGraph.
Retrieval Augmented Generation (RAG): Build and optimize RAG pipelines, including implementing and managing embeddings, vector databases, and advanced rerankers to enhance response quality and relevance.
Vibe Coding: Use code generation applications (e.g. Replit, Cursor, Google AI Studio, Git Hub Copilot in Agent mode, etc.) to create full applications (including frontend and backend), generate tests, perform testing and integrate them in the core product without writing any code.
LLM Fine Tuning: Lead efforts in LLM fine-tuning (e.g., LoRA, QLoRA) for specific domain knowledge and tasks, and implement strategies for and efficiency.
Prompt Engineering: Develop and refine advanced prompt engineering techniques to maximize model performance, consistency, and safety.
Full-Stack Development: Own end-to-end implementation from frontend to the backend.
Java (Plus): Expose AI/LLM functionality written in Python using Java services, leverage multi-threading capabilities in Java to augment AI/LLM functionality developed in Python
Code Quality & Productivity: Utilize AI-powered development tools (e.g., GitHub Copilot, etc.) to efficiently generate, refactor, and optimize high-quality code.
Collaboration: Work closely with team leads managers, QA, product managers and team in the US (this will require the willingness to work overlapping with US working hours)
Qualifications
Undergraduate degree in Computer Science or similar Engineering field, advanced degree is a plus
5+ years of professional experience in software development, with a minimum of 2 years focused on AI/ML development, particularly with LLMs
Strong proficiency in Python and its relevant data science libraries (e.g., Pandas, NumPy, Scikit-learn)
Proven experience integrating and working with major LLM APIs - both public and private/local, e.g., Gemini, OpenAI, Anthropic, Llama, Ollama, etc., including hands-on experience using techniques for LLM efficiency
At least 1 year of deep practical experience with LangChain and LangGraph for building complex LLM applications and agentic workflows using autonomous agents, tools, memory management, parallelization, etc.
Solid understanding and implementation experience with RAG architectures, vector DBs, vector search, embeddings, and reranking mechanisms
Experience leveraging AI Copilot or similar generative AI coding tools for accelerated development, code generation, refactoring, optimization, and vibe coding to create integrated backend and frontend applications
Experience creating UI using React and integrating the UI with the backend using REST APIs is a big plus
Hands-on experience with Java, especially integrating Java modules with Python modules is a nice to have, but not necessary
Role specific Questions
Please record and upload a video no longer than 3 minutes of yourself answering the following questions:
First ~60 seconds: Briefly explain your experience managing complex agentic workflows or RAG pipelines with major LLM APIs.
Second ~ 60 seconds: Walk us through a time you handled end-to-end implementation from frontend to backend using LLMs.
Final ~60 seconds: How do you use tools like Cursor or GitHub Copilot in Agent mode to generate and refactor high-quality code? Describe a feature you built 'vibe-style' (without manual coding) and how you integrated it with the rest of the product functionality
Regards,
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