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Salary: USD 170,000 - 220,000 / annual
Manifold is an AI platform for life sciences that accelerates the development and deployment of life-changing medicines. The company serves global research institutions and pharmaceutical companies, helping them operate faster and more effectively across target identification, clinical development, market access, and precision medicine workflows.
You will join the Core Platform team, a small senior group responsible for foundational services powering Manifold's data, compute, and workflow capabilities. This is a hands-on individual contributor role with significant influence over longer-term product architecture.
Key responsibilities:
- Design, build, and operate compute and workflow orchestration services, including AMI management, autoscaling, custom runtime environments, and third-party tool integration
- Collaborate with the SRE team to improve reliability and observability of core services; establish operational standards, alerting, and runbooks to shift from reactive to proactive ownership
- Mentor engineers and drive technical decisions through well-written artifacts, bringing cross-cutting perspective to improve team output
- Partner with Product, Forward Deployed Engineers, and account teams to translate enterprise requirements into durable platform capabilities
- Contribute to Manifold's AI-native platform vision by identifying industry trends and assessing their relevance to life sciences research
You will support active enterprise users and their AI agents analyzing genomics and life sciences datasets at scale. Your work directly impacts customer outcomes and accelerates breakthrough science.
REQUIREMENTS:
- 8+ years of enterprise software experience with meaningful time on backend, infrastructure-adjacent, or distributed systems work; demonstrated ownership of complex, scalable production systems
- Mastery of Python and deep infrastructure-as-code experience (Terraform)
- Experience managing compute environments on AWS (EC2, ECS, Batch, or equivalent), including autoscaling and cost/performance tradeoffs
- Ability to support a broad technical surface area and orient quickly in unfamiliar codebases
- Operational ownership mindset: care about production outcomes, build for observability from the start, close the loop on incidents with durable fixes
- Genuine integration of AI tools into your engineering workflow with concrete examples of impact
- Familiarity with bioinformatics workflows (WDL, Nextflow, Cromwell) is a plus
- Life sciences or regulated-industry experience is a plus
- Understanding of and genuine commitment to accelerating life sciences research
