AI Platform Engineer IV

sed on the Model Context Protocol (MCP) and AI Gateway patterns.

"I am the person Capital Group is looking for."

You can build and maintain AI platform services:

• Develop data ingestion pipelines, feature stores, and ML workflows

• Integrate vector databases, knowledge graphs, and model registries with governance

• Implement automated ML-Ops pipelines for training, evaluation, and deployment

• Design model serving infrastructure for real-time and batch inference and orchestrate agentic workflows using modular, extensible frameworks

• Enable agentic workflows and secure connectivity using MCP and AI Gateway patterns

• Integrate with agent orchestrators and support for agent-to-agent communication protocols

You ensure observability and responsible AI:

• Monitor model performance, data quality, and lineage

• Implement logging, alerting, and rollback mechanisms

• Apply explainability, fairness, and compliance guardrails

You have experience with embedding security and compliance:

• Integrate encryption, IAM, and audit logging

• Support compliance with regulatory and internal policies (e.g., GDPR, SOC 2, Responsible AI frameworks)

• Partner with InfoSec and data governance teams to ensure safe and compliant use of data and models

You drive operational excellence:

• Apply SRE and FinOps practices for reliability and cost optimization

• Automate infrastructure provisioning with IaC

You collaborate and enable teams:

• Partner with data scientists and engineers to deliver platform solutions

• Develop APIs, SDKs, and self-service tools for rapid experimentation

• Produce clear documentation, runbooks and architectural diagrams

Required Qualifications

• You have a bachelor's degree in computer science, Engineering or a related technical field or relevant experience.

• You have 5+ years of general platform technology build experience or large, distributed systems

• You have 3+ years of experience building, operating AI/ML platforms

• You possess hands-on experience with MLOps tools and ML frameworks

• You are well versed in vector databases and knowledge graph technologies

• You have familiarity with agentic AI frameworks and orchestration tools

• You have experience designing and implementing solutions based on the Model Context Protocol (MCP) and AI Gateway patterns

• You have proficiency in Python and/or other languages commonly used in AI/ML engineering

• You have experience with cloud platforms and container orchestration

• You have an understanding of AI observability, model monitoring, and responsible AI practices

• You have experience implementing security, privacy, and compliance controls in AI/ML environments

Preferred Qualifications

• Experience in regulated industries (e.g., financial services) and navigating governance, risk, and compliance for AI

• Familiarity with AI-specific observability tools

• Experience with agent orchestrators, agent-to-agent communication, and multi-agent systems

• Exposure to AI guardrails and responsible AI frameworks (e.g., explainability, bias detection)

• Experience with cost optimization and FinOps for AI/ML workloads

• Familiarity with Agile and DevSecOps practices in AI/ML environments

Southern California Base Salary Range: $153,965-$246,344

New York Base Salary Range: $163,212-$261,139

In addition to a highly competitive base salary, per plan guidelines, restrictions and vesting requirements, you also will be eligible for an individual annual performance bonus, plus Capital's annual profitability bonus plus a retirement plan where Capital contributes 15% of your eligible earnings.

You can learn more about our compensation and benefits here.

• Temporary positions in Canada and the United States are excluded from the above mentioned compensation and benefit plans.

We are an equal opportunity employer, which means we comply with all federal, state and local laws that prohibit discrimination when making all decisions about employment. As equal opportunity employers, our policies prohibit unlawful discrimination on the basis of race, religion, color, national origin, ancestry, sex (including gender and gender identity), pregnancy, childbirth and related medical conditions, age, physical or mental disability, medical condition, genetic information, marital status, sexual orientation, citizenship status, AIDS/HIV status, political activities or affiliations, military or veteran status, status as a victim of domestic violence, assault or stalking or any other characteristic protected by federal, state or local law.