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Alejandro Alemany
Senior Full-Stack AI/ML Engineer specializing in MLOps and GenAI
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Senior backend/data engineer who has built and maintained HIPAA-compliant, real-time clinical FastAPI services on AWS, orchestrating ML/LLM and vector DB calls with strong reliability patterns (auth, timeouts/retries, graceful degradation, idempotency). Also delivered AWS IaC/CI-CD (Terraform/Helm/GitHub Actions) across EKS/Lambda/SageMaker and built Glue/Spark ETL with schema evolution and data quality controls, plus demonstrated large SQL performance wins (15 min to <9 sec) and hands-on incident ownership.
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Key Strengths
- Built/maintained HIPAA-grade real-time clinical backend with strict uptime/latency requirements
- Designed reliable FastAPI services with OAuth2/JWT auth, KMS-managed secrets, and consistent middleware-based error handling
- Resilience patterns: explicit timeouts, exponential-backoff retries, graceful degradation, caching, and idempotent/transactional writes
- Event/data pipeline reliability using Kafka acknowledgements/retries and incremental/idempotent ETL design
- AWS delivery with Terraform+Helm IaC and GitHub Actions CI/CD deploying to EKS/Lambda/ECR
- Cost/performance optimization via autoscaling (HPA), reserved concurrency, workload separation, spot capacity, and spend alerting
- AWS Glue analytics pipeline with schema evolution controls and data quality validation
- Legacy modernization with parity validation (parallel runs), stakeholder sign-off dashboards, feature flags, and rollback
- SQL performance tuning with measured impact (15 minutes to <9 seconds) via indexing, partitioning, and query rewrites
- Production incident ownership: detected via CloudWatch alerts, triaged logs/metrics, mitigated with rerouting/reprocessing, prevented recurrence with schema validation
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2 publications
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