19 days ago
Remote, United StatesSenior
Base Salary
$195k - $260k/yr
Responsibilities
- Drive backend development for AI workflows using Python and FastAPI.
- Productionize LLM integrations, including quotas, retries, failover, cost controls, model configuration, and approval constraints.
- Design secure, auditable, compliant systems for customer data handling, tenant isolation, observability, and traceable AI outputs.
- Scale the platform through asynchronous job orchestration, performance tuning, and data-layer optimization.
- Build tenant-aware services, role-based access, SSO integrations, and administrative and reporting capabilities.
- Improve reliability with monitoring, tracing, alerting, and operational tooling for LLM pipelines and workflow execution.
- Implement real-time event delivery and publish/subscribe patterns for workflow state, notifications, and agent feedback.
- Contribute to platform architecture, shared-services decisions, and cross-stack integration boundaries.
- Translate evolving product and non-functional requirements into practical technical solutions with product, architecture, legal, and security stakeholders.
- Champion strong typing, automated testing, continuous integration, and schema-driven API contracts with typed client generation.
Requirements
- 7+ years of professional software development experience, including 5+ years building Python services in production.
- Deep experience with APIs, asynchronous processing, background jobs, and workflow orchestration.
- Cloud-native backend experience with AWS and services for compute, storage, networking, identity, secrets, encryption, and delivery automation.
- Experience productionizing distributed systems with reliability, observability, retries, throughput, failure handling, and performance tuning.
- Strong PostgreSQL and large-scale data-processing experience, including indexing, query tuning, and batch-versus-stream tradeoffs.
- Required experience with retrieval-augmented generation, vector search, and embedding-based systems.
- Experience with multi-tenant systems, role-based access control, audit logging, secure data handling, and regulated environments.
- Hands-on experience building LLM-driven workflows involving tool calling, state machines, human-in-the-loop approvals, checkpoint/resume, and multi-step orchestration.
- Experience with AI-native engineering workflows, prompt engineering, evaluation design, caching, token efficiency, and model-selection tradeoffs.
- Experience with or knowledge of Bedrock, OpenAI, Anthropic, LangChain, LangGraph, enterprise authentication, graph-shaped data, observability, and infrastructure as code is a strong plus.
- Ability to work from partial requirements, make pragmatic product-focused tradeoffs, and ship software based on real customer usage.
Tech Stack
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