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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Software Engineer, Search Backend - **Company:** Auction Technology Group - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $209,000 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Test Suite, Artificial Intelligence, Airflow, Amazon Web Services, Architectural Patterns, BigQuery, C Sharp (Programming Language), Data Files, Data Warehousing, Relational Databases, Distributed Systems, Elasticsearch, Python (Programming Language), PostgreSQL, Microsoft Message Queuing, MySQL, Query Optimization, Queueing Systems, RabbitMQ, Redis, Software Engineering, TypeScript, Workflow Management Systems, Datadog, Real Time Systems, Normalized Discounted Cumulative Gain, Snowflake, Indexer, Backend, Fastapi, Kotlin, Event Driven Architecture, Kubernetes, Apache Kafka, Restful APIs, Data Pipelines, Dynatrace, OpenSearch, Golang, Microservices - **Published:** November 1, 2026 - **Apply:** https://www.dice.com/job-detail/b2b67c0f-29cd-4125-8095-09a4bf31a250 ## About the Role 8+ years of professional software engineering experience with a focus on backend development (or 6+ years with a Master's degree, or a PhD with 3+ years, or equivalent) Expert-level Python with production experience building and operating scalable backend services; this is a must Production experience with at least one statically typed language (Go, Java, Kotlin, C#, or similar) in addition to Python Production experience with Elasticsearch or OpenSearch at scale: query DSL, index mappings and analyzers, performance/relevance tuning, and capacity planning A track record of owning the design and evolution of systems or significant components, applying architectural thinking to scalability, reliability, and maintainability Experience driving delivery across teams: decomposing complex problems into well-scoped initiatives, guiding sound technical trade-offs, and improving execution predictability Experience with relational databases (MySQL/PostgreSQL) including schema design, optimization, and query tuning Experience deploying and operating containerized services on Kubernetes Experience with workflow orchestration and batch data pipelines (Airflow or similar) Knowledge of message queuing systems (RabbitMQ, Kafka, AWS SQS/SNS) and event-driven architectures Strong understanding of RESTful API design, microservices architecture, and distributed systems Experience with testing frameworks and comprehensive test suites, and with observability tooling (Dynatrace/Datadog or similar) Experience with on-call rotation and incident management: able to independently triage incidents in your domain, without guidance, from alert to root cause and resolution, and to lead incident response when multiple teams are involved A record of mentoring senior-level engineers and contributing to hiring (interviewing, calibration, raising the bar) Clear understanding of how technical decisions impact operations, cost, and customer experience Familiarity with AWS cloud services Soft Skills: Leads cross-team initiatives and defines execution standards that improve consistency and scalability Makes data-backed decisions that impact multiple teams and medium-term objectives; develops strategic insight from data and experience Excellent communication skills: tailors messages to technical and non-technical audiences, from engineers to mid-management, and articulates trade-offs clearly Engages cross-functional teams to align on business priorities, influencing beyond immediate team boundaries Leads change initiatives: addresses resistance, secures buy-in, and reinforces long-term behavioral shifts Coaches and develops others; models engineering excellence in reviews, design discussions, and hiring Addresses cross-functional challenges with systemic process improvements rather than one-off fixes Proactive about technical investment: balances short-term delivery with long-term maintainability, and can defend the balance Nice-to-Have: Production experience with Go; several of our services are written in Go Exposure to TypeScript (you may occasionally touch front-end or tooling code) Search relevance and information-retrieval depth: BM25 tuning, ranking metrics (NDCG, CTR), learning-to-rank, vector or hybrid search Experience with data warehouses (Snowflake, Bigquery) and analytics pipelines Experience in eCommerce, marketplace, or auction platforms (e.g. LiveAuctioneers, Proxibid, Chairish); high-traffic or real-time systems ## Description Our stack is Python-centred (FastAPI services on Kubernetes) with Go services at the edges, Elasticsearch at the core, RabbitMQ-driven indexing, MySQL and Redis for supporting data, and Airflow-orchestrated batch workflows against our data warehouse. You'll shape technical direction with the engineering manager and architects, drive initiatives that span the search team and its neighboring teams (Product, Data, platform, and the marketplace front-ends), and mentor the Senior engineers around you. This is an opportunity to make a significant impact on a platform serving millions of users worldwide. Search is the front door of our marketplaces, and the systems you design directly move what buyers find, what sellers sell, and what the platform costs to run. Key Responsibilities What you'll be doing: Own the design and evolution of the search backend (query serving, indexing, and the ranking-signal data loop), introducing architectural patterns that improve scalability, reliability, and maintainability Stay hands-on: design, develop, and maintain scalable backend services and RESTful APIs in Python (FastAPI) powering search across our marketplaces Own and evolve how we query Elasticsearch (query construction, mappings and analyzers, relevance and ranking) for a catalog of tens of millions of live and historical listings, including capacity, latency, and cluster-cost trade-offs Drive the health and throughput of the event-driven indexing pipelines from RabbitMQ into Elasticsearch, setting the standards for freshness, blast-radius control, and replay/backfill safety Design batch and data workflows (Airflow, data warehouse) that compute ranking signals, search suggestions, and related searches feeding back into the live search experience Drive delivery across teams: decompose complex problems into well-scoped initiatives, identify risks early, improve predictability, and unblock others without becoming a bottleneck Determine when technical spikes and proof-of-concepts are needed, define their success criteria, and validate outcomes; sponsor and review spikes led by Senior engineers Set and raise engineering standards for the team: testing practices, deployment quality gates, observability (Dynatrace/DataSet), and incident readiness of a business-critical serving path Lead incident response for the search domain when it matters most, and turn incidents into prevention through post-incident improvements Weigh technical decisions against operations, cost, and customer experience; make the trade-offs explicit when proposing direction Integrate AI and automation into engineering workflows to improve productivity, quality, and early risk detection, with sound judgment about when not to rely on it Mentor Senior engineers and support their growth into broader technical ownership; act as a key technical interviewer and contributor to hiring decisions Write the technical documentation and decision records that let your architectural decisions survive contact with a growing organization