Senior Backend Engineer
Listed on 2026-02-28
-
Software Development
Data Engineer, Software Engineer
Description
About the RoleWe're looking for a Senior Backend Engineer to build and scale the GenAI Lens backend platform. This is a production-focused role centered on Mongo
DB data design and performance, scalable/durable data ingestion and processing pipelines, and operating high-throughput systems with strong observability and reliability. You'll also help build and evolve our API layer (Graph
QL and JSON-RPC).
Experience with Graph
QL is a strong plus, but the core focus is data systems and platform engineering. You should be comfortable working in a product that leverages modern AI technologies (embeddings, vector search, LLM integrations) and understand the practical standards that come with them-evaluation, guardrails, observability, and cost controls.
- Maintain and improve our data pipelines to keep data flowing reliably from ingestion to delivery
- Scalable, durable data ingestion and processing pipelines (event-driven, fault-tolerant workflows; retries, idempotency, backfills, and DLQs)
- Own data quality by implementing monitoring, alerting, and validation
- Design Mongo
DB schemas and query/index strategies for scale (aggregation pipelines, Atlas Search/vector search where relevant) - JSON-RPC data layer service that powers Graph
QL (designing/maintaining RPC methods, scaling throughput/latency, and evolving contracts safely) - Support AI-adjacent platform needs (embedding generation workflows, provider abstractions, prompt/model metadata, evaluation hooks)
- Own backend services end-to-end, from design and implementation through deployment and production support
- Deliver scalable Graph
QL resolvers with performance-aware patterns (batching, caching, pagination) - Build and evolve the JSON‑RPC data access layer for Graph
QL, including method design, backward compatibility, and performance tuning. - Own Mongo
DB performance: modeling, indexing, aggregation pipelines, and measurable latency/throughput targets - Build reliable serverless/event-driven components (idempotency, retries, DLQs, back pressure, rate limiting)
- Improve reliability and operational readiness (SLO‑minded engineering, incident response hygiene, runbooks)
- Partner closely with frontend, product, and UX to enable features cleanly and safely
- Drive code quality via testing, reviews, and CI/CD improvements
- Mentor engineers and influence engineering standards across the team
- Experience building and maintaining backend services in production
- Strong experience with Graph
QL APIs (schema design, resolver patterns, authorization, performance) - Strong experience with Mongo
DB (data modeling, indexing, aggregation pipelines; Atlas Search and Vector Search, sharding experience is a plus) - Strong proficiency with Node.js and JavaScript / Type Script
- Strong proficiency with Python (services, jobs, data processing, or tooling)
- Experience building on AWS, preferably serverless/event-driven architectures (Lambda, SQS/SNS/Event Bridge, S3)
- Experience working with high-traffic or business-critical systems
- Solid understanding of performance optimization techniques (caching, async processing, data access patterns)
- Experience with Terraform for production infrastructure (IAM, networking, secrets, repeatable environments)
- Experience with testing frameworks and pragmatic test strategy (unit, integration, contract)
- Familiarity with CI/CD pipelines (Git Hub Actions preferred; alternatives acceptable)
- Experience debugging, monitoring, and operating production systems
- Comfortable working in a distributed team environment
- Strong operational skills: logging, metrics, tracing, dashboards/alerts, and production support practices
- Cloud experience, preferably AWS, including:
- Lambda
- SQS / SNS / Event Bridge / Kafka
- S3
- Cloud Watch
- API Gateway (where applicable)
- Experience with Infrastructure as Code, preferably Terraform
- Experience with private networking patterns (VPC, security groups, Private Link/VPC endpoints) is a plus
- Exposure to containerized workloads (EKS/Kubernetes) is a plus, even if the core architecture is serverless-first
- Prior experience leading projects, features, or technical…
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