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Tellius

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2.6

based on 7 Reviews

6 Tellius Jobs

AI Engineer

Tellius

2.6

based on 7 Reviews

2-5 years

Remote

1 vacancy

AI Engineer

Tellius

posted 4mon ago

Job Role Insights

Key skills for the job

Data Analysis Data Analytics Python Excel SQL Automation Testing

+ 2 more

Job Description

Tellius is looking for an innovative AI Engineer to design and build a sophisticated conversational interface and agentic platform, which will bring the power of our advanced analytics directly into user interactions. This position calls for a strategic thinker and skilled engineer who is passionate about creating AI-driven experiences that feel intuitive and adaptable.

Key Responsibilities:

Develop, integrate, and optimize a conversational interface that allows users to interact naturally with Tellius, from querying insights to performing complex data tasks.
Build agentic systems that enable autonomous workflows, allowing users to conduct multi-step processes seamlessly through conversational prompts.
Implement and enhance Retrieval-Augmented Generation (RAG) capabilities, ensuring that the conversational interface pulls relevant, accurate information for real-time interactions.
Use frameworks like LangChain and LangGraph to structure conversational flows and develop agentic capabilities, enhancing the interface s responsiveness and personalization.
Collaborate with cross-functional teams to integrate the conversational interface with Tellius s broader analytics platform, ensuring a cohesive and high-performing user experience.

Requirements:

Strong experience with conversational AI, particularly LLMs, and natural language processing to drive intuitive, accurate interfaces.
Proven experience with agentic platforms and frameworks like CrewAI, AutoGen, LangChain, or LangGraph to build autonomous conversational agents.
Proficiency in Python and experience working in environments requiring high efficiency and optimized performance.
Hands-on experience with Retrieval-Augmented Generation (RAG) techniques and integration for conversational and agent-based platforms
Large Language Models (LLMs) : Experience with fine-tuning and deploying models like GPT-3/4, IBM Granite, or similar for text-to-SQL tasks.
Semantic Search and Vector Databases : Proficiency with vector databases (e.g., Chroma DB, Pinecone) and ranking algorithms (BM25, cross-encoder models).
A collaborative approach to problem-solving and an innovative mindset to bring new conversational and agentic capabilities to the platform.