Forward Deployment Engineer

Summary

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, where you will guide new clients through successful integration with our SaaS platform and manage client-specific configurations.

Responsibilities

• 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

Skills

• Hands-on experience using GitHub for version control
• Familiarity with YAML syntax and Helm charts for application configuration and deployment
• Working knowledge of Kubernetes (no deep expertise required, but willingness to learn)
• Experience writing shell scripts (e.g., Bash) for automation and troubleshooting
• Proficiency with SQL for data manipulation, reporting, and basic performance tuning
• Solid understanding of XML-based configurations and integrations
• Basic knowledge of SAML, SSO, and similar authentication and security protocols
• Familiarity with REST APIs and how they fit into broader integration strategies
• General understanding of networking fundamentals
• Excellent communication skills for client-facing interactions and the ability to explain complex concepts into clear, actionable guidance
• Demonstrated ability to manage multiple projects and adapt to shifting priorities
• Basic understanding of machine learning concepts and model deployment practices
• Ability to monitor AI solution performance and assist with troubleshooting and optimization
• Experience with financial crime, AML, KYC, or fraud detection solutions
• Coding experience in one of the main modern languages: python, java, etc…
• Understanding of DevOps, CI/CD, and cloud automation best practices
• Certification with any of the major cloud providers: GCP, AWS, Azure
• Understanding of AI model governance concepts such as explainability, auditability, and data privacy in production deployments

Qualifications

Must Haves

• Hands-on experience using GitHub for version control
• Familiarity with YAML syntax and Helm charts for application configuration and deployment
• Working knowledge of Kubernetes (no deep expertise required, but willingness to learn)
• Experience writing shell scripts (e.g., Bash) for automation and troubleshooting
• Proficiency with SQL for data manipulation, reporting, and basic performance tuning
• Solid understanding of XML-based configurations and integrations
• Basic knowledge of SAML, SSO, and similar authentication and security protocols
• Familiarity with REST APIs and how they fit into broader integration strategies
• General understanding of networking fundamentals
• Excellent communication skills for client-facing interactions and the ability to explain complex concepts into clear, actionable guidance
• Demonstrated ability to manage multiple projects and adapt to shifting priorities
• Basic understanding of machine learning concepts and model deployment practices
• Ability to monitor AI solution performance and assist with troubleshooting and optimization

Nice to Haves

• Experience with financial crime, AML, KYC, or fraud detection solutions
• Coding experience in one of the main modern languages: python, java, etc…
• Understanding of DevOps, CI/CD, and cloud automation best practices
• Certification with any of the major cloud providers: GCP, AWS, Azure
• Understanding of AI model governance concepts such as explainability, auditability, and data privacy in production deployments