Lead MLOps Engineer (Remote in MA)

In this position, you will lead the architecture, deployment, and operational strategy for production-grade AI services, machine learning platforms, and large language model (LLM) solutions. You will work closely with AI engineers, data teams, and platform engineers to create scalable, secure, and resilient infrastructure that supports both customer-facing and internal AI workloads., * Define architecture standards for model serving, agent execution, and scalable AI workloads

• Manage model lifecycle processes including deployment, versioning, promotion, rollback, and governance
• Build infrastructure supporting both real-time and batch AI processing
• Design secure, multi-tenant AI environments with strong data isolation controls
• Develop evaluation frameworks, testing pipelines, and release gates for AI systems
• Establish observability, monitoring, and operational excellence standards
• Drive platform reliability, scalability, and cost-efficiency initiatives
• Partner with engineering, security, and data teams to deliver enterprise-grade AI solutions
• Lead design reviews and provide technical mentorship to engineering teams
• Evaluate emerging AI technologies and make strategic build-versus-buy recommendations
• Contribute to infrastructure automation, CI/CD improvements, and deployment practices

• 10+ years of professional software engineering and infrastructure engineering experience
• Proven expertise designing and scaling cloud-native distributed systems in production environments
• Strong background leading technical architecture decisions for large-scale platforms
• Extensive experience building and operating AI/ML infrastructure as a customer-facing product
• Hands-on experience deploying and supporting LLM-based applications in production
• Deep knowledge of Retrieval-Augmented Generation (RAG), prompts, embeddings, and model lifecycle management
• Advanced programming skills in Python and TypeScript
• Experience with model deployment, versioning, and model-serving platforms
• Strong understanding of API architecture, REST services, and OpenAPI specifications
• AWS expertise and experience working with containerized environments such as Docker
• Experience with Infrastructure as Code tools, including CloudFormation or CDK
• Knowledge of observability, monitoring, alerting, tracing, and SLI/SLO/SLA practices
• Experience implementing security controls for multi-tenant environments, including PII and PHI protection
• Ability to mentor engineers and influence architecture across multiple teams

Desired Skills & Experience

• Familiarity with modern LLM orchestration frameworks
• Experience supporting agent-based AI systems in production
• Knowledge of model serving optimization, inference tuning, and cost management
• Experience with multimodal AI solutions involving image or scientific datasets
• Background in model optimization techniques such as quantization or distillation
• Experience working in regulated industries with compliance requirements
• Exposure to life sciences, healthcare, laboratory systems, or scientific data platforms
• Understanding of AI governance, evaluation frameworks, and quality monitoring

• Competitive base salary plus potential bonus eligibility
• Fully remote opportunity for candidates located in Massachusetts
• Opportunity to influence the architecture of a high-impact AI platform
• Leadership role with significant technical ownership and decision-making authority

You will receive the following benefits

• Medical Insurance
• Dental Benefits
• Vision Benefits
• Unlimited Paid Time Off (PTO)
• 401(k)
• Life Insurance
• Long-Term Disability Coverage
• Short-Term Disability Coverage

Motion Recruitment Partners (MRP) is an Equal Opportunity Employer. All applicants must be currently authorized to work on a full-time basis in the country for which they are applying, and no sponsorship is currently available. Employment is subject to the successful completion of a pre-employment screening. Accommodation will be provided in all parts of the hiring process as required under MRP’s Employment Accommodation policy. Applicants need to make their needs known in advance.