Senior Backend Engineer
About The Position
Benji is building the infrastructure layer for loyalty and brand connectivity. We enable companies to integrate, launch, and scale loyalty experiences across partners through a single platform—turning fragmented ecosystems into programmable networks. We work with leading enterprise brands and move fast to bring new partnerships and integrations to life. The Role We’re looking for a Senior Backend Engineer (or full stack with a strong backend emphasis) to own core platform services and help define how we build software in an AI-native way. This role sits at the intersection of: Backend platform engineering Distributed systems & event-driven architecture Partner integrations & API design AI-powered engineering workflows You will: Design, build, and extend Benji’s Python microservices across campaigns, users, rewards, orders, and partner integrations Own event-driven workflows, data integrity, and cross-service orchestration at production scale Build and evolve AI-native engineering standards - agents, MCP tooling, and LLM-powered product workflows This is not a maintenance role - you’ll be building the core infrastructure that powers loyalty flows for enterprise brands.
Requirements
- 7+ years of experience as a backend or full-stack engineer with a strong backend focus
- Comfortable owning services end-to-end - from API design through database schema, event handling, deployment, and debugging
- Strong Python backend experience and solid understanding of distributed systems
- You care about correctness in production systems and enjoy untangling integration complexity
- You’re an AI-first engineer - you already use agents and LLMs in your daily workflow, and you’re excited to help a team adopt that at scale
- You’re excited about building scalable, enterprise ready systems.
- Strong Python backend experience (Flask or similar frameworks)
- Production experience with PostgreSQL, REST APIs, and event-driven architectures (queues, pub/sub, async consumers)
- Solid understanding of distributed systems: idempotency, retries, eventual consistency, and webhook reliability
- Experience deploying and operating services on AWS (ECS, RDS/Aurora, SQS, S3, or equivalent)
- Hands-on experience working with LLMs and AI developer tooling as part of how you build software
- Experience building or integrating: AI agents, LLM-powered workflows MCPs, CLIs or similar context/tooling layers
- Familiarity with prompt design, tool use, and integrating LLMs into real product workflows
- Strong interest in making AI a first-class part of engineering culture, not an afterthought
Nice To Haves
- Experience with loyalty, fintech, commerce, or API platform domains (Stripe, Plaid, Square, etc.)
- Terraform and infrastructure-as-code experience
- Elasticsearch or search/analytics read models
- Vue/TypeScript comfort for occasional full-stack work
- Experience authoring agent context
- Experience with AWS Bedrock or other managed LLM APIs in production
- OpenTelemetry / observability tooling (Coralogix, Datadog, etc.)
Responsibilities
- Design, build, and extend Benji’s backend microservices using our layered architecture
- Build and maintain Python based APIs with OpenAPI docs, authentication, and strict schema contracts
- Implement event-driven workflows via messaging brokers
- Own relational and non relational schema design, migrations, and data integrity across services
- Extend shared platform libraries and uphold cross-service conventions
- Build reliable integrations with loyalty programs, payment platforms, and commerce systems (REST, OAuth, webhooks)
- Handle real-world edge cases: rate limits, retries, idempotency, reconciliation, and data inconsistencies
- Design abstractions that normalize messy partner APIs into clean Benji domain models
- Own webhook delivery, token lifecycle, and secure credential handling
- Deploy and operate services such as ECS Fargate, Aurora PostgreSQL, Redis, S3, and Elasticsearch
- Work with Terraform to evolve infrastructure as the platform grows
- Instrument services with OpenTelemetry and structured logging
- Own integration tests and maintain high confidence in cross-service behavior
- Design and maintain agent-ready engineering standards: in house rules, skills and relevant AI oriented documentation
- Build and evolve MCP servers and agent tooling that give our clients’ AI systems safe, accurate context into their Benji integration
- Integrate LLMs into product workflows
- Experiment with and adopt new AI dev tooling (Cursor agents, copilots, code generation workflows) to improve velocity across the team
- Write prompts, tool definitions, and guardrails that make AI output production-grade
- Champion AI native workflows across our engineering and product teams.
Benefits
- Competitive salary + equity
- Health, dental, vision
- Flexible work environment
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
