Back-End Software Engineer

BackOps-AI•San Francisco, CA

6h•Hybrid

About The Position

BackOps AI is transforming supply chain operations with agentic AI solutions that automate complex workflows, freeing operations teams to focus on what matters most. Headquartered in the San Francisco Bay Area with flexible remote-friendly options, we foster a culture of innovation, ownership, and measurable impact. As a Back-End Software Engineer (preferrably Python), you’ll design, build, and operate the backend systems that power our agentic workflows—reliable services, APIs, data pipelines, and integrations that turn messy operational reality into scalable execution. You’ll help shape microservices patterns, data foundations, and production reliability as we scale customers and workloads.

Requirements

Experience: 4+ years building backend services in production, primarily in Python
Python Depth: Strong experience building production APIs/services in Python; comfortable with performance tuning, profiling, and pragmatic engineering tradeoffs
Microservices Depth: Strong understanding of distributed systems fundamentals and microservices patterns (service boundaries, dependency management, failure isolation)
Database Expertise: Solid knowledge of relational databases (schema design, indexing, query optimization, transactions) and comfort with data modeling for evolving products
Pragmatic Builder: Comfortable navigating ambiguity, making tradeoffs, and delivering iteratively in an early-stage environment
Integration Mindset: Experience with external APIs and enterprise systems; strong instincts around failure modes and reliability
Ownership & Communication: Clear written/verbal communication; able to explain architecture decisions and partner with non-technical stakeholders
Security & Quality: Committed to secure development practices, code reviews, and maintainable code

Nice To Haves

Node.js: Experience building backend services in Node.js (useful for interoperability with parts of our stack)
Experience with event-driven architectures, message queues, workflow orchestration, or background job systems
Observability experience (structured logging, tracing, metrics) and operational excellence in production
Familiarity with SOC 2-oriented controls, data retention/deletion requirements, or regulated environments
Experience supporting AI/agentic systems via tools/APIs, guardrails, and workflow state management

Responsibilities

Microservices & APIs (Python): Design and implement backend services in Python using microservices patterns (clear service boundaries, contract-first APIs, versioning, backwards compatibility)
Resilient Workflow Systems: Build orchestration and integration layers with strong reliability practices (idempotency, retries, rate limiting, backoff, timeouts, circuit breakers)
Databases & Data Modeling: Design schemas, indexes, and queries; optimize performance; manage migrations; ensure consistency and data integrity across services
Queues, Jobs, and Events: Implement background jobs, queues, and event-driven workflows; ensure safe concurrency and predictable execution
Integrations: Build and maintain integrations with customer systems (e.g., ticketing/CRM/warehouse/shipping) and external APIs with robust error handling and observability
POC to Production: Own backend proof-of-concepts—define requirements, implement the core, iterate quickly, and harden into production with stakeholders
Quality, Security, and Reliability: Write secure code, review peers’ changes, strengthen testing, monitoring, and incident readiness
Operational Ownership: Participate in incident response as needed; contribute to documentation and lessons learned
Compliance Support: Maintain confidentiality, integrity, and availability aligned with BackOps.ai information security and privacy policies, including customer data retention and deletion processes

Benefits

Equity & Ownership: Competitive equity so you grow alongside the company
Impact & Visibility: Direct access to co-founders; your work drives real operational outcomes
Collaborative Culture: Tight-knit team of seasoned operators and AI experts
Flexible Work: Hybrid with core Bay Area presence and remote flexibility

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