We are seeking a senior MLOps Architect to design and scale a modern ML and Generative AI platform across AWS. This role will own the architecture for traditional ML and LLM/Generative AI pipelines, ensuring production reliability, governance, cost optimization (FinOps), and enterprise-grade security. The ideal candidate has deep expertise in AWS, SageMaker, Databricks, Atlan (data catalog/governance), and modern MLOps tooling, and understands how to operationalize LLMs, RAG systems, and foundation models within a governed, scalable MLOps stack. This is a strategic, hands-on architecture role responsible for integrating GenAI capabilities into an enterprise ML platform.
What you'll Do:MLOps & GenAI Platform Architecture - Design and implement scalable ML and LLM infrastructure on AWS (SageMaker, EKS, S3, IAM, Lambda, Step Functions, CloudWatch).
- Architect end-to-end ML and Generative AI lifecycle workflows:
- Data ingestion & preprocessing o Feature engineering / embedding generation o Model training & fine-tuning (traditional ML + foundation models)
- Model evaluation & validation
- Deployment (real-time, batch, streaming)
- Monitoring & retraining
- Integrate LLM pipelines (prompt workflows, RAG architectures, fine-tuning flows) into the enterprise MLOps stack.
- Define standards for CI/CD/CT pipelines across ML and GenAI workloads.
Generative AI & LLM Operationalization- Architect Retrieval-Augmented Generation (RAG) pipelines including:
- Embedding generation workflows
- Vector database integration
- Document ingestion and chunking strategies
- Retrieval evaluation and monitoring
- Design and deploy LLM-based services using:
- Managed services (e.g., SageMaker endpoints, Bedrock-style APIs)
- Containerized custom inference services
- Establish prompt versioning, evaluation frameworks, and experiment tracking for LLM systems.
- Implement guardrails for hallucination control, safety monitoring, bias detection, and usage logging.
- Define architecture for LLM fine-tuning workflows (including data curation, evaluation, and cost controls).
- Implement scalable orchestration of LLM pipelines using workflow engines and event-driven patterns.
Deployment, Monitoring & Reliability- Architect scalable inference patterns for:
- Traditional ML models
- LLM APIs
- RAG systems
- Implement model monitoring frameworks for:
- Performance degradation
- Drift detection
- LLM output quality
- Latency and token usage metrics
- Define SLAs/SLOs for ML and GenAI systems.
- Design safe deployment strategies (blue/green, canary, shadow testing).
- Establish logging, observability, and traceability standards for GenAI systems
FinOps & Cost Optimization- Implement cost tracking for:
- Training workloads o GPU utilization
- Inference endpoints o Token consumption (LLM APIs)
- Vector database storage
- Optimize LLM workloads for cost-performance tradeoffs (model size, batching, caching strategies).
- Design autoscaling and compute optimization strategies for GPU and CPU-based inference.
- Partner with finance and engineering teams to forecast ML/GenAI infrastructure spend.
Platform Enablement & Standards- Define enterprise standards for:
- Experiment tracking
- Model registry
- Prompt registry
- Artifact management
- Embedding versioning
- Provide architectural guidance to data science, AI, and engineering teams.
- Evaluate and recommend tooling across the ML/GenAI stack (MLflow, feature stores, vector databases, orchestration tools).
- Drive documentation and reusable patterns for ML and GenAI development.
What We're Looking for- 6+ years of experience in ML engineering, data engineering, or MLOps roles.
- Proven experience architecting ML platforms in AWS.
- Strong hands-on experience with SageMaker (training, pipelines, deployment).
- Experience operationalizing LLM or Generative AI systems in production.
- Experience building RAG pipelines and integrating vector databases.
- Experience working with Databricks in production.
- Experience implementing data governance and catalog systems (e.g., Atlan).
- Strong understanding of CI/CD principles for ML and GenAI.
- Experience with containerization (Docker) and orchestration (Kubernetes/EKS).
- Deep knowledge of infrastructure-as-code (Terraform, CloudFormation).
- Strong understanding of observability and monitoring for ML systems.
- Experience implementing cloud cost optimization strategies (FinOps).
- Strong Python proficiency.
- Experience with foundation model fine-tuning and parameter-efficient methods.
- Experience implementing model registries and experiment tracking tools.
- Experience designing feature stores and embedding stores.
- Familiarity with AI risk management, bias mitigation, and safety controls.
- Experience supporting regulated or data-sensitive environments.
- Platform-level architectural thinking.
- Deep understanding of how to integrate GenAI into enterprise ML ecosystems.
- Ability to balance scalability, governance, security, performance, and cost.
- Strong technical leadership and cross-functional collaboration skills.
- Hands-on ability to move from architecture design to implementation
Kapitus Total Rewards Package Includes: - Competitive Base Salary Range of $117,800 - $189,000 Kapitus is providing this as a good faith salary range to comply with applicable law. The applicant's final salary will depend on a number of factors including the applicant's geographic location, skills, and experience.
- Annual Incentive Compensation Eligibility -Up to 10% annually
- Health Insurance: Comprehensive medical, dental, and employer-paid vision plans through UnitedHealthcare (UHC), with various coverage levels available to meet the needs of our employees and their families. Additional perks through UHC include: Sweat Equity, free subscription to the Calm App, UHC rewards, Real Appeal, and Quit For Life.
- Flexible Spending Account: Set aside pre-tax dollars from your paycheck to pay for qualified out-of-pocket medical, dental, vision, pharmacy or dependent care expenses.
- Lifestyle Spending Account: Employer sponsored post-tax benefits that allow reimbursement for expenses related to physical, mental and financial well-being.
- 100% Company Paid Insurances: Kapitus fully covers the cost of basic short-term and long-term disability insurance, as well as vision insurance, ensuring our employees have comprehensive protection without any personal expense.
- Voluntary Insurance: Supplemental life insurance as well as enhanced short- and long-term disability coverage are available through Mutual of Omaha, providing additional security for our employees. Additionally, Colonial Accident and Hospitalization insurances are also available, offering further protection against unforeseen events.
- Paid Maternity and Parental Leave: Beyond state-mandated leave policies, Kapitus provides company-paid maternity and parental leave, supporting our employees during important family milestones.
- Commuter Benefits: We offer pre-tax benefits on parking and commuter expenses to cover travel to and from work.
- LifeBalance Program: Enhance your lifestyle with our LifeBalance membership, which offers discounts on outdoor activities, the arts, health, and fitness. Additional benefits include:
- Pet and car insurance discounts.
- Financial services such as LegalShield.
- Relaxation and stress management tools.
- Plum Benefits Discount Program: Access exclusive discounts on shows, travel, car rentals, and more, enriching your personal and family life.
- Tuition Reimbursement: Pursue further education with up to $5,000 annually in tuition reimbursement, plus opportunities to attend relevant conferences and career development events. Managed through our LSA plan, Kapitus Academy.
- Travel Reimbursement: We also offer travel reimbursement for all work-related travel, supporting your involvement in career and personal development activities.
- Paid Time Off and Sick Time.
- Retirement Benefits: Our 401K plan is managed through Fidelity. To support your long-term financial goals, the company provides a 25% match on your contributions, up to 6% of your annual salary.
Consideration will be given to qualified remote candidates residing in states where Kapitus and/or one of its subsidiaries has an established physical presence.
