Python Developer

Responsibilities
Define technical requirements with product, business, and engineering stakeholders
Design, develop, and maintain production-grade Python applications and backend services
Build asynchronous, API-driven services using technologies such as FastAPI and asyncio
Design scalable APIs and microservices for internal and external consumers
Own solutions from design through implementation, testing, deployment, monitoring, and production support
Design for reliability, scalability, maintainability, and fault tolerance
Apply distributed-system patterns including caching, queues, event-driven processing, and background workloads
Diagnose production issues using logs, metrics, tracing, profiling, and other observability tools
Participate in code reviews, contribute to engineering standards, and best practices
Collaborate with engineering, QA, product, design, and business teams to deliver high-quality releases
Maintain clear technical documentation for architectures, APIs, and workflows
Use AI-assisted development tools to improve engineering productivity and code quality
Applied AI / LLM Focus
Build and productionize LLM-enabled capabilities such as classification, extraction, intelligent routing, workflow automation, and conversational experiences
Integrate commercial and open-source LLM APIs into reliable production services
Build tool/function-calling interfaces that safely connect AI systems with backend services and business workflows
Design multi-step AI workflows with state management, validation, retries, fallbacks, and deterministic application logic
Use structured outputs and validation to make LLM behavior predictable and testable
Implement retrieval and ranking approaches such as embeddings, vector search, semantic retrieval, re-ranking, and RAG where appropriate
Build evaluation frameworks using representative datasets, regression tests, quality metrics, and production feedback
Optimize AI systems for latency, reliability, cost, and quality
Implement appropriate guardrails, observability, data controls, and auditability
Evaluate when an LLM is appropriate versus deterministic logic, classifiers, or traditional software approaches
Requirements:
7+ years of professional software engineering experience with significant hands-on Python development in production
Strong Python fundamentals, including data structures, exception handling, typing, testing, and maintainable application design
Strong understanding of asynchronous and concurrent Python, including async/await, event-loop behavior, task management, timeouts, and blocking operations
Experience building production APIs and microservices using FastAPI, Flask, Django, or similar frameworks
Strong understanding of REST APIs, service integrations, authentication/authorization, and secure API design
Experience designing and operating distributed backend systems using patterns such as queues, caching, pub/sub, retries, idempotency, and fault tolerance
Ability to troubleshoot complex production issues across application code, infrastructure, and external dependencies
Experience with logging, metrics, tracing, alerting, automated testing, CI/CD, and containerized deployments
Strong familiarity with Git and modern code-review practices
Ability to independently own significant technical work from problem definition through production
Strong written and verbal communication skills and the ability to explain technical decisions and tradeoffs
Ability to work effectively in a collaborative, cross-functional environment

Work arrangement
Yes