Senior Backend Engineer

About Benji

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.

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
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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.

• 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 Open Telemetry 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.

• 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…