Forward Deployment Engineer

SymphonyAI is a leading provider of financial services software, offering advanced solutions in compliance and fraud detection.

We are looking for a dynamic and innovative Forward Deployment Engineer to join our Professional Services team.

As a Forward Deployment Engineer in our Professional Services Team, you will be instrumental in guiding new clients through a smooth and successful integration with our SaaS platform and implementations on client premises.

You will leverage your knowledge of modern development, deployment, and security practices to manage client-specific configurations, ensure optimal performance within our infrastructure, and help clients understand how to utilize our product suite effectively.

This role requires adaptability, strong communication skills, and the ability to balance multiple client engagements.

• Collaborate with clients and internal teams to onboard them in our FinTech platform seamlessly and within the agreed schedule.
• Work with automation tools (GitHub, YAML, Helm) to package, deploy, and configure applications in Kubernetes (basic to intermediate knowledge).
• Create and maintain shell scripts and SQL queries to support integration, troubleshooting, and reporting.
• Develop and review XML-based configurations and data exchange schemas.
• Participate in technical meetings with clients, discussing SAML, SSO, REST APIs, Architecture Design, and basic networking considerations.
• Advocate and implement best practices for version control, CI/CD pipelines, and deployment patterns.
• Research emerging technologies and proactively identify areas for improvement.
• Provide ongoing support, troubleshooting, and documentation for deployed solutions.
• Deploy AI/ML models as part of compliance solutions, including model endpoints and integration with existing infrastructure.
• Assist with data preparation, validation, and feature engineering for AI applications, ensuring high-quality inputs for model performance.
• Educate and train clients on how to interpret and leverage AI-powered features and outputs.
• Troubleshoot and monitor deployed AI solutions, identifying issues such as data drift, model degradation, or unexpected output, and escalate where necessary.