
Lead Python Platform Software Architect
1 week ago
About the Role:
We are seeking a seasoned Python Engineer to lead our platform architecture and drive performance optimization.
- Job Responsibilities:
- Platform Architecture:
- Design and build a shared component library for data pipelines, including ingestion, parsing, extraction, validation, enrichment, and publishing.
- Establish standardized patterns/templates for Apache Beam pipelines and Databricks jobs, ensuring consistency in configuration, packaging, versioning, CI/CD, and documentation.
- Implement pluggable interfaces to enable multiple teams to swap extractors, OCR providers, and EMR publishers without code rewrites.
- Performance and Reliability:
- Oversight of end-to-end profiling and tuning, leveraging cProfile, py-spy, line_profiler, memory (tracemalloc), CPU vs I/O analysis.
- Instrumentation of services with Elastic APM and correlation with Splunk logs; building dashboards and runbooks for monitoring and troubleshooting.
- Implementation of concurrency best practices: asyncio for I/O-bound tasks, ThreadPool/ProcessPool for CPU-bound tasks, batching, rate limiting, retries, etc.
- Robust LLM API rate limiting/governance: enforcing provider TPM and concurrency caps, request queueing/token budgeting, and emitting APM/Splunk metrics (throttle rate, queue depth, cost per job) with alerts.
- Team Enablement:
- Mentoring developers, leading design reviews, codifying best practices, and writing clear documentation and examples.
- Partnering with ML engineers on the future LLM/SLM path (evaluation harness, safety/PII, cost/perf).
- Platform Architecture:
Expertise You'll Bring:
- 7+ years of Python experience with strong depth in performance and concurrency (asyncio, concurrent.futures, multiprocessing), profiling, and memory tuning.
- Observability expertise: Elastic APM instrumentation and dashboarding; Splunk for logs and correlation; OpenTelemetry familiarity.
- Must have implemented LLM-based solutions and supported them in production.
- API engineering for high-throughput integrations (REST, OAuth2), resilience patterns, and secure handling of sensitive data.
- Strong architecture/design skills: clean interfaces, packaging shared libraries, versioning, CI/CD (GitHub Actions/Azure DevOps), testing.
- 3+ years building large-scale data pipelines with Apache Beam and/or Spark, including hands-on Databricks experience (Jobs, Delta Lake, cluster tuning).
- Document processing: OCR (Tesseract, AWS Textract, Azure Form Recognizer), PDF parsing, text normalization.
- LLM/SLM integration experience (e.g., OpenAI/Azure AI, local SLMs), prompt/eval frameworks, PII redaction/guardrails.
- Cloud and tooling: AWS/Azure/GCP, Dataflow/Flink, Terraform, Docker; cost/performance tuning on Databricks.
- Security/compliance mindset (HIPAA), secrets management, least-privilege access.
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