Senior Backend Engineer

B5 Recruiting•Austin, TX

About The Position

We are looking for a Senior Backend Engineer to help design, build, and support scalable backend systems for a modern data-driven software platform. This role is focused on production backend engineering, data architecture, API development, distributed processing, and operational reliability. The ideal candidate has strong experience building backend services, working with large-scale data flows, improving database performance, and supporting systems in production. This person should be comfortable working on a product that includes modern AI-enabled features, including search, embeddings, model integrations, and related platform workflows. In this role, you will help improve the backend platform that supports data ingestion, processing, APIs, search, and production application workflows. Key areas of focus include: * Building and maintaining reliable backend services * Improving data ingestion and processing workflows * Designing scalable database models, indexes, and query patterns * Supporting API layers used by frontend and product teams * Building and maintaining service-to-service data access patterns * Improving system performance, reliability, and observability * Supporting AI-adjacent workflows such as embeddings, vector-based search, provider integrations, evaluation hooks, and metadata management * Helping improve infrastructure, deployment, testing, and operational practices

Requirements

Strong experience building and maintaining backend services in production
Strong experience with API development, including GraphQL or similar API patterns
Experience with schema design, resolvers, authorization, pagination, batching, caching, and API performance optimization
Strong experience with MongoDB or similar document-oriented databases
Experience with data modeling, indexing, aggregation pipelines, query optimization, and performance tuning
Strong proficiency with Node.js, JavaScript, and/or TypeScript
Strong proficiency with Python for services, jobs, automation, data workflows, or internal tooling
Experience with cloud-based backend systems, preferably AWS
Experience with serverless, event-driven, or asynchronous architectures
Experience with services such as queues, object storage, event buses, cloud functions, monitoring tools, and API gateways
Experience with high-traffic, business-critical, or production-scale systems
Solid understanding of backend performance patterns, including caching, async processing, connection management, and data access optimization
Experience with Infrastructure as Code, preferably Terraform
Experience with production testing strategies, including unit, integration, and contract testing
Familiarity with CI/CD pipelines and modern deployment workflows
Strong debugging, monitoring, incident response, and production support skills
Comfortable working in a distributed team environment
Must be an expert in Mongo DB
Must be an expert in Python, Node.JS and Typescript
Experience with AI coding tools

Nice To Haves

Experience with very high-throughput backend systems
Experience tuning concurrency, connection pools, and service latency
Experience with search, analytics, saved views, filters, or precomputed data patterns
Experience with database scaling, sharding, or large data sets
Experience with multi-region or compliance-conscious architectures
Experience refactoring legacy systems or consolidating services for performance and cost efficiency
Experience improving cloud cost, reliability, and operational efficiency
Candidates do not need to be machine learning researchers, but should understand how AI-powered software features are built, integrated, and supported in production.
Embeddings and vector-based search concepts
Integrating with external AI, LLM, or embedding providers
Designing abstractions around third-party providers
Handling timeouts, retries, fallbacks, and rate limits
Understanding cost, latency, quality, and relevance tradeoffs
Supporting evaluation, regression checks, observability, guardrails, and auditability
Using AI developer tools to improve engineering speed, testing, quality, or maintainability

Responsibilities

Own backend services from design through deployment and production support
Build and improve APIs with attention to performance, scalability, security, and maintainability
Design and maintain backend service contracts and data access patterns
Improve database performance through data modeling, indexing, aggregation/query optimization, and latency reduction
Build reliable event-driven and asynchronous processing workflows
Implement retries, idempotency, failure handling, dead-letter queues, rate limiting, and backpressure where needed
Improve system observability through logging, metrics, tracing, dashboards, alerts, and runbooks
Partner with product, frontend, design, and engineering teams to deliver features safely and efficiently
Improve testing, code quality, CI/CD, and engineering standards
Mentor other engineers and contribute to architecture and technical decision-making