Open | Cloud-Native | Purpose-Built for Science
Senior Software Platform Engineer
Location
United States
Posted
3 days ago
Salary
0
Seniority
Senior
Job Description
Senior Software Platform Engineer
TetraScience
Role Description We’re looking for a Senior AI Platform Engineer to help design, build, and scale our AI and data infrastructure. In this role, you’ll focus on architecting and maintaining cloud-based MLOps pipelines to enable scalable, reliable, and production-grade AI/ML workflows, working closely with AI engineers, data engineers, and platform teams. Your expertise in building and operating modern cloud-native infrastructure will help enable world-class AI capabilities across the organization. If you are passionate about building robust AI infrastructure, enabling rapid experimentation, and supporting production-scale AI workloads, we’d love to talk to you. - 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). Qualifications - 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. Nice to Have - 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. Benefits - 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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