Python Developer

Tech Rakers
San Antonio, United States of America
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

San Antonio, United States of America

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Cloud Computing
Continuous Integration
Data Stores
Distributed Systems
Github
Python
PostgreSQL
MySQL
OAuth
OpenID
Performance Tuning
Redis
Software Engineering
Data Streaming
Openapi
Google Cloud Platform
Enterprise Software Applications
Amazon Web Services (AWS)
Flask
Build Server
Backend
FastAPI
Containerization
Low Latency
Api Gateway
Amazon Web Services (AWS)
Terraform
Webhooks
Docker

Job description

Role: Build, operate, and scale Python APIs and backend services that integrate AI capabilities (e.g., Google Gemini via Vertex AI) to power internal and external applications. You will not build models; you'll productionize integrations, orchestrations, and data flows around them.

What You'll Do

  • Design, implement, and document FastAPI services and SDKs for AI features.
  • Integrate third-party AI providers (Gemini, Bedrock, OpenAI) with secure, observable patterns.
  • Build event-driven and synchronous backends (REST/webhooks/queues) with robust error handling.
  • Optimize latency, throughput, and cost; add caching, rate limiting, and retries/circuit breakers.
  • Ship high-quality code with tests, CI/CD.
  • Instrument services (structured logs, metrics, traces) and own production readiness/runbooks.
  • Collaborate with product, data, and ML teams to translate requirements into APIs and workflows.
  • Uphold security, privacy, and compliance (secrets, OAuth/OIDC, PII handling).

Requirements

  • 4-8+ years software engineering (mid-senior); strong Python 3.x.
  • Production FastAPI (or Flask) delivering secure, versioned APIs.
  • Cloud experience on Google Cloud Platform or AWS (e.g., Cloud Run/GKE/Pub/Sub or Lambda/EKS/API Gateway/SQS).
  • Datastores: Postgres/MySQL and one of Redis/ElastiCache/Memorystore; migrations and schema design.
  • CI/CD (GitHub Actions/Cloud Build), containerization (Docker), IaC familiarity (Terraform helpful).
  • Testing culture (unit/integration/contract), API specs (OpenAPI), and observability.
  • Strong grasp of resiliency patterns and performance tuning in distributed systems.

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