Senior Software Platform Engineer, MLOps - Cambridge. MA

Job Description A fast-growing technology company in the life sciences space is seeking a Senior Software Platform Engineer, MLOps to help build and scale the infrastructure powering enterprise AI and machine learning solutions. This role sits at the intersection of cloud platform engineering, distributed systems, and modern AI operations.
You will work closely with AI engineers, data teams, and platform engineers to design, deploy, and operate production-grade AI services used by external customers in highly regulated environments. This is a hands-on engineering position focused on building reliable, scalable, secure systems that support model serving, agent workflows, retrieval-augmented generation (RAG), observability, and AI lifecycle management.
The ideal candidate has a track record of owning critical platform components in production and has experience operating AI systems that support real-world users at scale. Required Skills & Experience

• 7+ years of software engineering and infrastructure engineering experience
• Strong background building distributed, cloud-native systems in production environments
• Production experience with AI/ML infrastructure, model deployment, and lifecycle management
• Hands-on experience deploying and operating LLM-based applications in production
• Experience with RAG architectures, embeddings, model versioning, and tool/function calling
• Strong Python and TypeScript development skills
• Experience designing and building REST APIs and OpenAPI-based services
• Experience with AWS cloud services and containerized workloads
• Familiarity with Infrastructure as Code tools such as CloudFormation or AWS CDK
• Experience implementing CI/CD pipelines and deployment automation
• Experience with observability, monitoring, logging, alerting, and distributed tracing
• Experience supporting multi-tenant platforms and handling sensitive data
• Strong communication skills and ability to contribute to technical direction

Desired Skills & Experience

• Experience with Databricks MLflow
• Experience with model registries, versioning, and model serving platforms
• Experience building AI evaluation frameworks and quality monitoring systems
• Knowledge of AI security practices including prompt injection protection and tool abuse prevention
• Experience supporting regulated environments requiring auditability and reproducibility
• Experience mentoring engineers and leading technical design reviews
• Experience evaluating AI frameworks, model providers, and serving technologies

What You Will Be Doing Daily Responsibilities

• 100% Hands On
• Design, build, and operate AI platform services and APIs
• Own model and prompt lifecycle management across production environments
• Develop infrastructure supporting model serving, inference, and agent-based systems
• Implement RAG capabilities and AI-powered workflows
• Build evaluation, testing, and quality assurance tooling for AI systems
• Establish monitoring, alerting, logging, and observability standards
• Partner with security teams to implement AI and platform security controls
• Build scalable, multi-tenant cloud services supporting enterprise customers
• Develop Infrastructure as Code and deployment automation solutions
• Participate in architecture reviews and technical design discussions
• Create documentation and mentor engineers across the organization
• Support production reliability, performance optimization, and incident response

The Offer

• Competitive base salary of $170,000 - $220,000
• Equity opportunity
• Flexible work arrangements
• Unlimited PTO
• 401(k)
• Company-paid life and disability insurance

You will receive the following benefits

• Medical Insurance
• Dental Benefits
• Vision Benefits
• Paid Time Off (PTO)
• 401(k)

Applicants must be currently authorized to work in the US on a full-time basis now and in the future. Sponsorship is not available for this position.