More than a mission, C2FO is a better financial system changing the way every business gains access to the working capital they need to thrive. At C2FO, everyone is an employee-owner which means we're all invested in our work and team members. We're a company of team players and self-starters finding new and innovative ways to get things done. If you're excited to learn, grow, and leave your mark on our fast-growing organization, C2FO may be the place for you.
About C2FO
Headquartered in Kansas City, USA, C2FO has more than 500 employees worldwide, with operations throughout North America, Europe, India, Asia Pacific, and Australia. C2FO is the world's largest on-demand working capital platform. Our mission is to ensure every business has the capital needed to thrive and we have delivered more than $400+ billion in funding to businesses since our founding. How do we do this By providing fast, flexible, and equitable access to low-cost capital through our easy-to-use platform.We provide technology with a human touch, giving our customers the direct support they need and ensuring our team members have the tools, resources, and work environment they need to deliver on our promise to customers. With the C2FO platform, businesses worldwide have more working capital to fuel their growth, create jobs and develop new products.
Benefits
At C2FO, we take care of our customers and our people the vital human capital that helps our customers thrive. That's why we offer a comprehensive benefits package, flexible work options for work/life balance, volunteer time off, and more. Learn more about our benefits here. (https://www.c2fo.com/amer/us/en-us/about-us/careers
Designation: Senior AI Platform Engineer_REMOTE
Location: Remote
Responsibilities (The AI Platform Mindset)
- Centralized Orchestration: Design and implement a robust engineering foundation to host all AI agents and models within Amazon Bedrock, ensuring they are governed, scalable, and deployable across various product lines.
- Platform over Projects: Move the team away from bespoke, manual model deployments toward a standardized AI Platform model. Build Internal AI Services and tools to empower underserved functions like Sales, Legal, Finance, and Accounting.
- CI/CD & DataOps: Establish automated MLOps pipelines for model training, evaluation, and deployment. Partner with Data Engineering to ensure DataOps readiness for high-performance AI features.
- Augmentation & Governance: Work with our business and product teams to build human-in-the-loop (HITL) workflows that augment, not automate, ensuring all AI features are safe, transparent, and compliant.
- Operational Excellence: Optimize and scale machine learning infrastructure (AWS/Kubernetes) to support high-performance model training and inference while reducing the operational debt of existing GenAI/ML models.
Qualifications
Must Have
- 5-7 years of software engineering experience with strong system design skills
- 2-3 years building and operating production LLM systems, including RAG or agent workflows
- Led the design and delivery of at least one end-to-end GenAI system from ideation to production
- Deep expertise in building AI agents, specifically managing state, long-term memory, and multi-turn context
- Hands-on experience with LLM integration, prompt engineering, structured outputs, and evaluation frameworks, including proficiency with orchestration tools like LangChain and/or LangGraph.
- Have built APIs or internal platforms that expose AI capabilities to multiple teams with cost and latency optimization
- Strong understanding of CI/CD, Infrastructure as Code, and distributed system design to support scalable AI platforms
- Proficient in Python and at least one additional language such as TypeScript
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field
Nice to Have
- Experience with AWS, including Bedrock and related AI services
- Experience with Docker and Kubernetes-based deployments
- Experience with microservices or cloud-native architectures
- Hands-on experience with ETL processes, data pipelines, and data warehousing solutions
- Experience building AI systems in regulated or compliance-driven domains
