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Open | Cloud-Native | Purpose-Built for Science
Senior Software Platform Engineer
Location
United States
Posted
82 days ago
Salary
0
Seniority
Senior
Job Description
Senior Software Platform Engineer
TetraScience
• 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).
Job Requirements
- 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.
- Strong knowledge of AWS and infrastructure-as-code frameworks, ideally with CDK.
- 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.
- 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 such as DSPy 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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