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MaintainX, now part of Autodesk Operations Solutions, is a mobile-first work execution platform serving 13,000+ customers including Duracell, McDonald's, Shell, DHL, and Volvo. The platform manages 13.9 million assets and 79.5 million completed work orders, helping industrial and frontline teams cut unplanned downtime and optimize operations.
You will design and build MaintainX's end-to-end search and retrieval platform, spanning indexing pipelines, ranking systems, and AI-facing query layers. Working closely with product and domain experts, you'll model search across core entities like work orders, assets, and procedures to deliver high-relevance results. You'll ship fast, iterate based on feedback, and continuously improve the system.
Key responsibilities include operating and optimizing distributed systems for reliability, performance, and scalability under production load; driving architectural decisions that balance correctness, performance, and maintainability; owning integrations between search systems and upstream data sources; and exploring semantic search, vector retrieval, and AI-enhanced relevance using modern ML tooling. You'll also participate in on-call duties (currently business hours).
This role requires hands-on expertise in designing, building, and operating production-grade search systems end-to-end. You'll take systems from implementation through deployment and production operation, working across backend services, data pipelines, and integration points. Expert-level English (spoken and written) is essential, as you will lead platform engineering managers across multiple teams, present technical priorities to executive stakeholders, and align with engineering leaders outside Québec daily.
REQUIREMENTS:
- Hands-on production experience designing, building, and operating search systems end-to-end (indexing, query execution, relevance tuning, infrastructure) using Elasticsearch, OpenSearch, Lucene, Solr, or similar technologies
- Understanding of embeddings, chunking, and retrieval strategies
- Familiarity with search-specific tuning: analyzers, BM25, shard sizing, cluster health, and relevance optimization
- Comfort taking systems from implementation to deployment and production operation across backend services, data pipelines, and integration points
- Expert-level English proficiency, both spoken and written
NICE TO HAVE:
- Experience evaluating and improving search relevance using qualitative analysis and quantitative metrics
- Experience shipping AI-powered or LLM-integrated backend systems
- Comfort using modern AI tools (GPT, Copilot, Cursor) to boost productivity
- Understanding of multi-tenancy and data security (ACLs, field-level access controls, secure index partitioning)
- Experience building observability and success metrics into systems
