Python - Backend Developer

Role Summary

Design and ship Python backends that power AI-driven applications. Youll partner with AI engineers (LLM/RAG/agent teams) to turn prototypes into secure, scalable, observable servicesAPIs, workers, and event pipelinesthat integrate with enterprise systems such as SAP, Salesforce, and ServiceNow.

Responsibilities

• Build and maintain REST/gRPC APIs with FastAPI (or Flask + Pydantic), using asyncio for I/O-heavy paths. • Implement background jobs & schedulers (Celery/RQ/Arq) and event pipelines with Amazon SQS/SNS. • Model data with SQLAlchemy (2.x) + Alembic; performance tuning for Amazon RDS (SQL Server); caching with ElastiCache (Redis). • Wrap AI components (LLM endpoints, tool/function calling, RAG services) behind stable interfaces; handle streaming, retries, and timeouts. • Integrate with enterprise applications (SAP/Salesforce/ServiceNow/Workday) using OAuth2/OIDC, robust error handling, and idempotency keys. • Enforce security & compliance using Okta for IAM, AWS Secrets Manager for credential storage, and structured input validation (JSON Schema). • Build APIs and services that integrate with AWS Bedrock models, custom RAG services, and OpenSearch Serverless vector stores. • Ensure backend observability through OpenTelemetry and Datadog, including metrics, tracing, and logging.

  • Own operability aspects—feature flags, blue-green/canary release support, incident response workflows, and crisp documentation.

Must-Have Experience

• 3–5 years backend development in Python.
  • FastAPI (preferred) or Flask with Pydantic models; OpenAPI/Swagger API design. • Async programming (async/await), concurrency patterns, connection pooling, and backpressure management. • Database expertise with Amazon RDS (SQL Server/PostgreSQL) and Redis; schema design, indexing, query optimization; migrations with Alembic. • Event-driven architecture experience using Amazon SQS and Amazon SNS. • API security and integration design with OAuth2/OIDC, JWT, and rate limiting. • Containerized application development with Docker (deployment managed by platform team on Amazon EKS). • Testing: pytest, fixtures, mocks/stubs, contract tests, and load testing (k6/JMeter). • Observability: OpenTelemetry, Datadog, structured logging, and actionable alerts. • Solid understanding of secrets and identity management with AWS Secrets Manager and Okta.

Nice to Have

• Built streaming chat endpoints (SSE/WebSockets) and function/tool-calling adapters for AI services.
  • Worked with OpenSearch Serverless, Bedrock Knowledge Base, or other vector databases for RAG workflows. • Experience integrating backend systems with AWS Bedrock models and NeMo Guardrails for runtime safety. • Exposure to Kong API Gateway, feature flags (LaunchDarkly/Flipt), or policy-as-code (OPA). • Multi-tenant controls (RBAC, quotas, usage metering) and enterprise-grade integration patterns. • Familiarity with enterprise APIs (SAP OData/BAPI, Salesforce REST/Graph, ServiceNow).

Tech Stack (our core; equivalents welcome)

• Python 3.11+, FastAPI, Pydantic v2, SQLAlchemy 2.x, Alembic, pytest.
  • Amazon SQS/SNS for messaging and events. • Amazon RDS (SQL Server/PostgreSQL) for relational data, ElastiCache (Redis) for caching. • AWS Bedrock for model hosting and RAG services. • Amazon S3 for data storage, Amazon ECR for container images. • OpenSearch Serverless for vector storage and search. • AWS Secrets Manager, Okta IAM for authentication and secrets. • NeMo Guardrails on Amazon EKS for runtime safety. • Datadog + OpenTelemetry for observability and monitoring. • Kong API Gateway for service routing and access control. • Custom RAG Service and LLM evaluation using Phoenix/Arize/Promptfoo.