Senior Software Platform Engineer (MLOps)

Location: Hybrid in Cambridge, Massachusetts, or San Mateo, California, United States

Salary: $170,000–$220,000 USD per year

Company

hirify.global is building a scientific data and AI cloud for biopharma, providing secure and compliant infrastructure for enterprise scientific data and AI capabilities.

What you will do

• Design, build, and operate cloud services and APIs for running models and agents against customers’ scientific data.
• Own model and prompt lifecycle workflows across Databricks MLflow and AWS Bedrock, including registration, versioning, promotion, rollback, and multi-model serving.
• Build real-time and batch inference infrastructure with routing, batching, caching, concurrency control, capacity planning, large-binary handling, and graceful degradation.
• Integrate LLMs into production using RAG, tool and function calling, MCP-based tooling, and agent runtimes.
• Implement security, evaluation, observability, reproducibility, lineage, and auditability for regulated multi-tenant AI systems.
• Own production readiness, infrastructure-as-code, deployment automation, incident response, design documentation, technical direction, and mentoring.

Requirements

• 7+ years of professional software and infrastructure engineering experience building and operating distributed, cloud-native production systems.
• Technical ownership of significant services or components, including scalability, performance, and cost decisions.
• Production experience building and maintaining AI/ML infrastructure and model deployment and lifecycle management for users outside your own team; experience limited to internal team pipelines is not sufficient.
• Production experience with LLM systems, including RAG architecture, retrieval and embedding design, prompt and model versioning, and tool or function calling under real traffic and latency constraints.
• Experience securing multi-tenant platforms, enforcing tenant authorization boundaries, handling PII and PHI, and addressing prompt injection and tool abuse.
• Strong TypeScript and Python skills for reliable APIs and backend services, including reviewing AI-generated code for correctness, security, and fit.
• Production experience with a model registry and serving stack, ideally Databricks MLflow, including registration, versioning, asset bundles, and serving workflows.
• Experience using AI evaluation as a release gate, with evaluation harnesses, regression gates, and drift or quality monitoring for non-deterministic systems.
• Experience designing scalable, secure, versioned, and extensible REST and OpenAPI APIs; AWS, Docker, CloudFormation or CDK, CI/CD, observability, SLI/SLOs, monitoring, alerting, and distributed tracing.
• Clear communication with customers and cross-functional teams, with the ability to influence technical direction without direct management authority.

Culture & Benefits

• Flexible working arrangements within the hybrid role structure.
• Competitive compensation and stock options in a VC-backed Series C company.
• 100% employer-paid benefits for eligible employees and immediate family members.
• 401(k), unlimited paid time off, company-paid life insurance, and LTD/STD coverage.
• Visa sponsorship is not available for this position.