Senior Software Engineer

Senior Software Engineer - Platform AI Infrastructure

Picture a company redefining how life sciences harness data one that turns the noise of fragmented scientific systems into clarity that accelerates discovery, development and ultimately, human progress.

They are a pioneer in Scientific Data Cloud, building a cloud?native ecosystem engineered specifically for life sciences, connecting laboratory instruments, informatics systems and analytics applications into a single, intelligent network. Trusted by the worlds leading biopharma innovators, their open platform serves as the digital nervous system for scientific operations, enabling researchers to unlock insights at unprecedented scale.

Were building next?generation AI platform that empowers scientists and engineers to operationalize advanced machine learning models at global scale, operating at the intersection of life sciences, cloud computing and AI.

ATTN Please read carefully: We can not sponsor new visas or transfer existing visas. We are only considering US citizens or green card holders.

100% Remote However we require our team to be co?located in the Boston, MA area for occasional design meetings. If you are not located in Boston, MA your resume will not be considered.

What Youll Do

As a Senior Platform Engineer, youll help architect and build our clients proprietary, next?generation AI platform their internal equivalent to AWS SageMaker. This platform will serve as the foundation for developing, training and deploying advanced AI models across global scientific and biopharma environments.

Much like SageMaker, this system will enable teams to:

• Rapidly build, train and deploy AI models at scale
• Seamlessly integrate data pipelines for high?volume ingestion and transformation
• Deliver secure, reliable and production?grade AI workflows across distributed cloud infrastructure
  

Youll collaborate across data, AI and engineering teams to design resilient systems that power the companys most ambitious machine learning and scientific data initiatives enabling automation, scalability and operational excellence at the intersection of AI and life sciences.

Responsibilities

• Architect, build and maintain cloud?native infrastructure for AI and data workloads using platforms like Databricks and AWS Bedrock.
• Develop scalable data pipelines to ingest, transform and serve data for ML, analytics and scientific applications.
• Implement infrastructure?as?code using tools such as CloudFormation and AWS CDK to ensure consistency and security.
• Partner with AI engineers and data scientists to optimize model deployment, monitoring and performance.
• Lead observability best practices, including advanced monitoring, alerting and logging across AI systems.
• Evolve the AI platform to support emerging frameworks, data modalities and use cases.
• Research and recommend cutting?edge tools and approaches to improve scalability, cost?efficiency and speed.
• Integrate AI and LLM?based architectures (e.g., retrieval?augmented generation) into production environments.
  

What You Bring
Preferred Experience

• Familiarity with emerging LLM orchestration frameworks (e.g., DSPy) for complex prompt pipelines.
• Experience with vector databases / embedding stores (e.g., OpenSearch, Pinecone) for semantic search and retrieval.
• Understanding of LLM cost optimization, latency reduction and usage analytics at scale.
  

Required Experience

• 7+ years of professional experience in software or infrastructure engineering, including production AI systems.
• Proven expertise in building and maintaining ML infrastructure, including model deployment, lifecycle management and automation.
• Deep knowledge of AWS and modern infrastructure?as?code frameworks (ideally CDK).
• Expert?level proficiency in TypeScript and Python for backend and API development.
• Hands?on experience with Databricks MLFlow, including model registration, versioning and serving.
• Strong understanding of containerization (Docker), CI/CD pipelines and orchestration tools (e.g., ECS).
• Demonstrated ability to design secure, scalable, and fault?tolerant infrastructure for real?time and batch AI workloads.
• Excellent communication skills and the ability to collaborate effectively with cross?functional teams.
  

Seniority Level

Mid?Senior level

Employment Type

Full?time

Job Function

Engineering and Information Technology

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