TetraScience

Senior Software Platform Engineer

Rol remoto de Platform Engineering con fit claro de ubicación del candidato.

Publicado14 jul 2026

Países elegibles1 país aceptado

Señal de senioritySenior

Modelo de trabajoRemoto

Ubicaciones aceptadas para candidatos

Estados Unidos

Resumen del rol

Contenido del rol extraído en secciones para revisar más rápido.

Design, implement, and maintain cloud-native platform to support AI and data workloads, with a focus on AI and data platforms such as Databricks and AWS Bedrock.
Build and manage scalable data pipelines to ingest, transform, and serve data for ML and analytics.
Develop infrastructure-as-code using tools like Cloudformation, AWS CDK to ensure repeatable and secure deployments.
Collaborate with AI engineers, data engineers, and platform teams to improve the performance, reliability, and cost-efficiency of AI models in production.
Drive best practices for observability, including monitoring, alerting, and logging for AI platforms.
Contribute to the design and evolution of our AI platform to support new ML frameworks, workflows, and data types.
Stay current with new tools and technologies to recommend improvements to architecture and operations.
Integrate AI models and large language models (LLMs) into production systems to enable use cases using architectures like retrieval-augmented generation (RAG).

7+ years of professional experience in software engineering and infrastructure engineering.
Extensive experience building and maintaining AI/ML infrastructure in production, including model, deployment, and lifecycle management.
Expert-level coding skills in TypeScript and Python building robust APIs and backend services.
Production-level experience with Databricks MLFlow, including model registration, versioning, asset bundles, and model serving workflows.
Expert level understanding of containerization (Docker), and hands on experience with CI/CD pipelines, orchestration tools (e.g., ECS) is a plus.
Proven ability to design reliable, secure, and scalable infrastructure for both real-time and batch ML workloads.
Strong knowledge of AWS and infrastructure-as-code frameworks, ideally with CDK.
Ability to articulate ideas clearly, present findings persuasively, and build rapport with clients and team members.
Strong collaboration skills and the ability to partner effectively with cross-functional teams.

Familiarity with emerging LLM frameworks for advanced prompt orchestration and programmatic LLM pipelines.
Understanding of LLM cost monitoring, latency optimization, and usage analytics in production environments.
Knowledge of vector databases / embeddings stores (e.g., OpenSearch) to support semantic search and RAG.

100% employer-paid benefits for all eligible employees and immediate family members
Unlimited paid time off (PTO)
401K
Flexible working arrangements - Remote work
Company paid Life Insurance, LTD/STD
A culture of continuous improvement where you can grow your career and get coaching

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