Senior Software Engineer, Pipeline Team

🕒 Junho 6

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Foundation AI

SiteLinkedInTodas as Vagas

51 - 200 funcionários

Fundada em 2019

🤖 Inteligência Artificial

⚖️ Jurídico

💳 Fintech

💰 Seed Round em 2019-04

Artificial Intelligence • Legal • Fintech

A Foundation AI é uma empresa de tecnologia inovadora que se especializa na automação do processamento de documentos recebidos para a indústria de litígios e reclamações. Utilizando inteligência artificial avançada, a Foundation AI otimiza a classificação, indexação e encaminhamento de documentos, aprimorando significativamente a eficiência operacional de escritórios de advocacia e departamentos de reclamações. Ao fazer isso, permite que as organizações reduzam tempos e custos de processamento, permitindo que as equipes se concentrem em trabalhos de maior valor e melhorem a produtividade geral.

Descrição

• Design, build, and maintain end-to-end ML pipelines covering data ingestion, preprocessing, model training, evaluation, and serving. • Own model versioning, data versioning, and prompt versioning across environments. • Build and operate side-by-side deployment infrastructure and A/B testing frameworks to evaluate model variants in production with rigorous statistical guardrails. • Implement drift detection, data quality monitoring, and alerting across the pipeline stack. • Extend CI/CD practices to the ML lifecycle—automating training triggers, evaluation gates, and deployment workflows integrated with the broader engineering delivery pipeline. • Design and implement robust, high-performance, and secure ML infrastructure. • Provide mentorship and guidance to junior engineers, foster a culture of knowledge-sharing, and influence ML engineering best practices at the team and organizational level. • Ensure code quality through peer reviews, unit testing, and adherence to coding standards across pipeline and platform code. • Work closely with ML scientists, product managers, and infrastructure teams to translate model development needs into reliable production systems. • Ensure pipelines and model artifacts follow best security practices and industry compliance standards relevant to legal document processing. • Maintain clear technical documentation for pipelines, model registry conventions, and operational runbooks.

🎯 Requisitos

• 5+ years in software engineering, with at least 2–3 years in ML engineering, MLOps, or AI platform roles. • Hands-on experience with model versioning, data versioning, prompt versioning, experiment tracking, and deployment automation in production environments. • Proficiency with workflow orchestration (Apache Airflow or equivalent), experiment tracking (MLflow or equivalent), and cloud-based model hosting (AWS Bedrock or equivalent). • Experience designing and operating side-by-side deployments, shadow mode evaluation, canary releases, and automated rollback strategies for ML models. • Familiarity with model drift detection, data quality monitoring, and pipeline alerting; experience defining and tracking ML-specific SLOs. • Experience with AWS services (S3, ECS/EKS, Lambda, Step Functions, or equivalents); comfort operating in a cloud-native environment. • Proficient in Python; writes scalable, maintainable, and secure code. • Experience with SQL and familiarity with data engineering patterns is a plus. • Experience extending CI/CD principles to ML workflows, including automated training pipelines, evaluation gates, and model promotion flows. • Designs modular, high-performance systems; able to drive technical decisions and articulate trade-offs clearly. • Implements automated testing for pipeline components; values reproducibility and reliability in ML systems. • Tackles ambiguous, complex challenges; evaluates trade-offs across performance, reliability, and development velocity.

🏖️ Benefícios

• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Professional development opportunities