At SymphonyAI, we are committed to creating a safer future by leveraging cutting-edge technology to combat financial crime. Our team is driven by a shared vision to protect the connected world and deliver intelligent global solutions across an evolving landscape of financial crime challenges. We are passionate problem solvers, bringing together brilliant minds to make a meaningful difference every day. Together, we strive to make the world a safer place, where every day matters.
Job Description
What You Will Be Doing
As a Senior Engineering Manager, you will play a pivotal role in leading our Product Engineering group, which is central to our efforts in financial crime detection and compliance. You will lead, coach, and inspire a global team of skilled software engineers, ensuring they have the support and opportunities to excel. Your expertise in team organization, development, delivery management, cloud architecture, and machine learning operations (ML Ops) will be critical to our success. Key responsibilities include:
Team Organization & Development:
- Foster a collaborative culture aligned with our business purpose and strategy.
- Lead capacity planning, recruitment, and succession planning efforts.
- Manage onboarding, upskilling, and training plans for team members.
- Shape and facilitate engineering communities to promote knowledge sharing and consistency across agile teams.
- Provide career management support, including coaching, development planning, and performance reviews.
Delivery Management:
- Optimize team assignments into agile delivery teams aligned with priorities and backlogs.
- Support delivery teams in overcoming impediments and managing risks, issues, and dependencies.
- Collaborate with Product Management and Engineering to create high-level release delivery plans.
- Manage product releases and related deliverables, including organizing sales and marketing activities for released product versions.
Cloud Architecture & CloudOps:
- Define and implement cloud architecture best practices to ensure scalability, reliability, and security of our software solutions.
- Oversee cloud operations (CloudOps) to optimize performance, monitor resource usage, and manage costs effectively.
- Drive adoption of cloud-native technologies and practices across engineering teams.
Machine Learning Operations (ML Ops):
- Establish and optimize machine learning workflows, including data ingestion, model training, and deployment.
- Implement monitoring and governance frameworks to ensure the reliability and performance of machine learning models in production.
- Collaborate with data scientists and ML engineers to streamline the development and deployment of machine learning solutions.
Familiarity with Relevant Software Technologies:
- Typescript, React, Java EE, Kafka, Spark/Scala, Python.
- Containerization tools (e.g. Docker, Kubernetes, Openshift).
- Cloud Services (Azure, AWS, GCP).
- Application Servers (e.g., JBoss/Wildfly).
- Databases/SQL (PostgreSQL, Oracle).
- RestAPI/GraphQL.
- CI/CD tools (e.g., Jenkins, GitHub Actions, Azure DevOps).
- Source code management tools (GitHub, Git/Bitbucket).
- Test Tools (Selenium, JMeter).
Reporting and Stakeholder Management:
- Report delivery status to the CTO, including risks, issues, and dependencies.
- Communicate engineering progress and status to internal stakeholders.
- Liaise with other parts of the organization to align on business priorities and opportunities.
Skills and Experience
Essential:
- Master's or PhD in ICT, Engineering, Mathematics, or relevant field.
- 3+ years of experience managing and coaching a software development team.
- Experience in end-to-end software product development in a commercial environment.
- Familiarity with relevant software technologies and tools.
- Strong knowledge of agile software development principles and methods.
- Excellent communication skills and ability to connect with stakeholders at all levels.
- Demonstrated leadership and coaching abilities.
- Eagerness to dive into technical details when necessary.
- Willingness to travel as required.
- Experience in cloud architecture and cloud operations.
- Understanding of machine learning operations (ML Ops).
Nice to have:
- Financial services business or technology experience.
- Understanding of technical architecture approaches in enterprise solutions.
- Familiarity with agile tooling (e.g., Jira).
- Experience working in virtual teams across multiple locations.
- Hands-on experience in building or delivering software products.
About Us
SymphonyAI is building the leading enterprise AI SaaS company for digital transformation across the most critical and resilient growth industries, including retail, consumer packaged goods, financial crime prevention, manufacturing, media, and IT service management. Since its founding in 2017, SymphonyAI today serves 1500+ Enterprise customers globally and has grown to 2,500 talented leaders, data scientists, and other professionals across over 20 countries.
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