Senior Full-Stack AI Engineer
This is us
At Avenga, we believe that human creativity empowers technology that matters. Operating globally, our 6000+ specialists provide a full spectrum of services, including business and tech advisory, enterprise solutions, CX, UX and Ul design, managed services, product development, and software development.
This is you
Founding Engineer Mindset: You thrive in a 0-to-1 environment and are comfortable building end-to-end systems, from data ingestion to the user interface.
5+ years of professional experience in AI/ML Engineering or a related field, with a strong focus on Large Language Models (LLMs).
Deep expertise in Retrieval-Augmented Generation (RAG) architectures and the ability to design complex knowledge retrieval systems.
Strong proficiency in Python and experience orchestrating AI agents using frameworks like LangGraph.
Proven experience with Vector Databases (e.g., Pinecone, Chroma, Weaviate) for semantic search and memory.
Solid experience with Graph Databases, specifically Neo4j, for handling complex, interconnected data relationships.
Experience building data pipelines for scraping, ingesting, and processing massive, unstructured datasets (e.g., geological, geospatial).
Fluent English (spoken and written).
Ability to work with 1-2 hours daily overlap with the US PST timezone.
Nice-to-have skills:
Familiarity with 3D visualization libraries (e.g., Three.js, babylon.js) or map-based data visualization to help render data-driven insights directly in the UI.
This is your role
Architect End-to-End AI Systems: Design and build scalable pipelines that ingest massive geological datasets, process them using AI agents, and surface insights in an interactive user interface.
Implement Advanced RAG: Develop and optimize sophisticated RAG pipelines that combine vector search (Pinecone/Chroma) with graph database queries (Neo4j) to provide grounded, context-aware responses from complex data sources.
Build Agentic Workflows: Orchestrate multi-agent systems using LangGraph to automate complex tasks, such as data analysis, cross-referencing geological features, and report generation.
Develop Data Ingestion Pipelines: Create robust ETL processes for scraping, cleaning, and structuring large-scale, unstructured geological and geospatial datasets.
Integrate 3D/Map Visualizations: Collaborate on or lead the integration of data with 3D rendering libraries (Three.js, babylon.js) or mapping tools to transform raw AI outputs into intuitive, interactive visual insights for end-users.
Drive R&D: Evaluate and implement the latest advancements in LLMs, agentic frameworks, and knowledge graphs to solve novel challenges in data exploration.
Document and Lead: Clearly document system architecture, research findings, and development methodologies to ensure knowledge transfer and system maintainability.
What awaits you at Avenga?
At Avenga, everyone matters. We provide equal opportunities in recruitment, career development, and leadership, regardless of race, ethnicity, gender identity, sexual orientation, disability, age, religion, or any other characteristic. We are committed to fostering a work environment where our diverse community of employees, candidates, and business partners actively shapes our growth. By bringing together people from different backgrounds and experiences, we build a workplace where everyone feels free to be themselves while honoring the boundaries of others.
Apply To This Job
At Avenga, we believe that human creativity empowers technology that matters. Operating globally, our 6000+ specialists provide a full spectrum of services, including business and tech advisory, enterprise solutions, CX, UX and Ul design, managed services, product development, and software development.
This is you
Founding Engineer Mindset: You thrive in a 0-to-1 environment and are comfortable building end-to-end systems, from data ingestion to the user interface.
5+ years of professional experience in AI/ML Engineering or a related field, with a strong focus on Large Language Models (LLMs).
Deep expertise in Retrieval-Augmented Generation (RAG) architectures and the ability to design complex knowledge retrieval systems.
Strong proficiency in Python and experience orchestrating AI agents using frameworks like LangGraph.
Proven experience with Vector Databases (e.g., Pinecone, Chroma, Weaviate) for semantic search and memory.
Solid experience with Graph Databases, specifically Neo4j, for handling complex, interconnected data relationships.
Experience building data pipelines for scraping, ingesting, and processing massive, unstructured datasets (e.g., geological, geospatial).
Fluent English (spoken and written).
Ability to work with 1-2 hours daily overlap with the US PST timezone.
Nice-to-have skills:
Familiarity with 3D visualization libraries (e.g., Three.js, babylon.js) or map-based data visualization to help render data-driven insights directly in the UI.
This is your role
Architect End-to-End AI Systems: Design and build scalable pipelines that ingest massive geological datasets, process them using AI agents, and surface insights in an interactive user interface.
Implement Advanced RAG: Develop and optimize sophisticated RAG pipelines that combine vector search (Pinecone/Chroma) with graph database queries (Neo4j) to provide grounded, context-aware responses from complex data sources.
Build Agentic Workflows: Orchestrate multi-agent systems using LangGraph to automate complex tasks, such as data analysis, cross-referencing geological features, and report generation.
Develop Data Ingestion Pipelines: Create robust ETL processes for scraping, cleaning, and structuring large-scale, unstructured geological and geospatial datasets.
Integrate 3D/Map Visualizations: Collaborate on or lead the integration of data with 3D rendering libraries (Three.js, babylon.js) or mapping tools to transform raw AI outputs into intuitive, interactive visual insights for end-users.
Drive R&D: Evaluate and implement the latest advancements in LLMs, agentic frameworks, and knowledge graphs to solve novel challenges in data exploration.
Document and Lead: Clearly document system architecture, research findings, and development methodologies to ensure knowledge transfer and system maintainability.
What awaits you at Avenga?
At Avenga, everyone matters. We provide equal opportunities in recruitment, career development, and leadership, regardless of race, ethnicity, gender identity, sexual orientation, disability, age, religion, or any other characteristic. We are committed to fostering a work environment where our diverse community of employees, candidates, and business partners actively shapes our growth. By bringing together people from different backgrounds and experiences, we build a workplace where everyone feels free to be themselves while honoring the boundaries of others.
Apply To This Job