Senior Software Engineer - Search & AI
Guidepoint2 days ago
Toronto, CanadaSenior
Responsibilities
- Design Elasticsearch mappings, analyzers, tokenizers, queries, hybrid retrieval, and semantic search for expert and business data.
- Plan and execute reindexing, data fixes, alias cutovers, ingestion pipelines, and source SQL tuning.
- Operate Elastic Cloud deployments on Azure across production, QA, and development environments, including capacity, shards, ILM, snapshots, upgrades, and access controls.
- Monitor and troubleshoot search clusters using Datadog, Kibana, and Elasticsearch APIs, and lead incident response with root-cause analysis and follow-up fixes.
- Build inference services, LLM-powered query and filtering services, MCP servers, and relevance evaluation and A/B testing systems.
- Build and maintain Python APIs and workers running on AKS behind Azure APIM, including tests, deployments, scaling, dashboards, and alerts.
- Address security-scan findings, protect secrets, review code, create technical documentation, and mentor engineers on search and backend practices.
Requirements
- 6+ years of professional software engineering experience, largely building and operating backend systems in production.
- Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.
- 3+ years of hands-on experience with Elasticsearch, Solr, or OpenSearch, including cluster ownership, Query DSL, relevance tuning, aggregations, sizing, operations, and reindexing.
- Strong idiomatic Python 3 skills, including typing, async programming, packaging, pytest, and experience with Flask or FastAPI.
- Knowledge of data structures and algorithms, API design, concurrency, caching, SQL, testing, profiling, and distributed-system failure modes.
- Experience shipping features using embeddings or LLMs and operating embedding inference in production, with knowledge of lexical, semantic, and hybrid retrieval.
- Operational experience with Docker, Kubernetes, ideally AKS, CI/CD, observability, on-call work, cluster upgrades, and incident response.
- Clear written communication and ability to explain search behavior to non-engineers.
- Preferred qualifications include Elastic certification, Elastic 8.x vector search, ELSER, ES|QL, Solr or OpenSearch migrations, learning-to-rank, rerankers, relevance feedback, RAG pipelines, LLM agents, Logstash, Kafka, RabbitMQ, JMeter, k6, Azure tooling, Datadog, PHP, or TypeScript.
Benefits
- Hybrid work based in the Toronto office.
- Annual discretionary performance bonus eligibility.
- Paid time off.
- Comprehensive benefits plan.
- Company RRSP match.
- Development opportunities through LinkedIn Learning.
Tech Stack
Apache JMeterApache KafkaAzureDatadogDockerElasticsearchFastAPIFlaskKibanaKubernetesLogstashMicrosoft SQL ServerPHPPostgreSQLpytestPythonRabbitMQSQLTypeScript
Categories
About Guidepoint
Guidepoint provides on-demand expert consultations, surveys, events, and custom research that help investors, consultants, and corporate teams make informed decisions. It operates a large global network of subject-matter experts and offers access via subscriptions and project-based engagements. Founded in 2003 and headquartered in New York, the privately held company serves sectors including healthcare, consumer goods, technology, media and telecom, and energy.