Location: REMOTE / Montreal, Quebec
This job allows you to work remotely.
The company is a premier provider of specialized information management and collaboration solutions tailored for the Architecture, Engineering, Construction, and Owner (AECO) sectors. For over two decades, the organization has focused on solving the industry's most persistent challenge: the fragmentation of project data. By integrating disparate workflows into a unified environment, the company enables design and construction professionals to manage complex communication, documentation, and coordination tasks with total transparency. To date, their technology has been adopted by over 1,500 firms globally, supporting millions of users in the execution of more than 16 million projects worldwide.
Backed by a leading private equity firm, the organization delivers a mix of cloud-native and on-premises platforms designed to mitigate risk and boost operational efficiency. The software serves as a central nervous system for project delivery, having successfully indexed over one billion professional communications and managed millions of critical project actions like submittals and requests for information. In a landscape where nearly three-quarters of firms struggle with project delays due to siloed data, the company provides the essential connectivity required to ensure accountability, streamline handovers, and drive superior built-environment outcomes.
This role:
As an Agentic Developer, you will design and deploy autonomous AI systems that transform how construction professionals manage massive datasets. Leveraging frameworks like LangGraph and optimized vector databases, you will lead the development of Smart Email Filing and semantic search capabilities to automate classification and information discovery across billions of project artifacts. This hands-on role focuses on building production-ready agents that understand complex industry workflows and learn from user behavior, empowering hundreds of thousands of global users to eliminate data silos and drive superior project efficiency.
You will:
Agentic AI Development
•Design autonomous agents and multi-agent systems using LangGraph, LangChain, or CrewAI to power intelligent email filing and contextual search.
•Build complex orchestration workflows featuring conditional logic, tool-calling, memory systems, and human-in-the-loop interactions.
•Implement collaborative agent patterns to automate metadata extraction and intelligent communication routing.
LLM Integration & Optimization
•Optimize LLMs (OpenAI, Claude, Bedrock) through sophisticated prompt engineering, chain-of-thought reasoning, and evaluation frameworks.
•Manage high-volume production workloads by balancing latency, cost, and token usage while implementing robust fallback strategies.
Vector Databases & Semantic Search
•Architect and tune vector databases (Pinecone, Weaviate, or OpenSearch) to enable hybrid search across billions of project artifacts.
•Develop efficient chunking, embedding, and re-ranking strategies to maximize retrieval accuracy and context preservation.
Indexing & Data Pipelines
•Build scalable, real-time indexing pipelines using CDC patterns to keep vector indexes synchronized with source systems.
•Design automated document preprocessing and enrichment workflows to ensure high-quality data normalization and metadata extraction.
RAG (Retrieval-Augmented Generation) Systems
•Design production-grade RAG architectures that integrate citation tracking, source verification, and automated retrieval quality metrics.
•Create feedback loops and evaluation frameworks to continuously improve the relevance of AI-generated responses.
Production Deployment & Collaboration
•Deploy agentic microservices on AWS (Lambda, ECS, or EKS) ensuring multi-tenancy, observability, and secure API integration.
•Partner with Product, Data, and Backend teams to translate user needs into production AI capabilities within an Agile environment.
•Maintain comprehensive documentation for agent architectures and participate in on-call support for production systems.
Must Have Skills:
• 4+ years of software engineering experience with at least 2 years focused on AI/ML or LLM applications
• Strong hands-on experience building production systems with LLMs (OpenAI, Anthropic, AWS Bedrock, or similar)
• Proven experience with agentic AI frameworks, particularly LangGraph, LangChain, or similar agent orchestration tools
• Expertise with vector databases (Pinecone, Weaviate, pgvector, Qdrant, ChromaDB, or Amazon OpenSearch) including optimization and tuning
• Experience building indexing pipelines for document processing, embedding generation, and search systems
• TypeScript, C# and Python programming skills with experience in async programming and API development
• Hands-on experience with AWS services including Lambda, ECS, S3, DynamoDB, and EventBridge
• Understanding of RAG (Retrieval-Augmented Generation) architectures and best practices
• Knowledge of prompt engineering, few-shot learning, and LLM optimization techniques
• Experience with semantic search, embedding models, and similarity metrics
• Familiarity with document processing, text extraction, and NLP techniques
• Strong problem-solving skills and ability to debug complex AI systems
• Excellent communication skills and ability to explain AI concepts clearly
• Passion for building practical AI solutions that solve real user problems
