So sorry, this position is no longer available.
Please go ahead and submit your application. We may have other positions that would be the perfect fit for you.
Alternatively, you may want to apply to one of the following related jobs:
Our client is seeking a high-caliber Lead Full Stack Engineer to join their organization. You will lead a high-performing agile team dedicated to designing, building, and maintaining scalable applications for global financial ecosystems. You will work across the entire stack—front-end, back-end, infrastructure, and data—to deliver secure, reliable, and innovative software solutions.
Key Responsibilities
Architectural Leadership: Lead the design of complex, distributed full-stack systems to improve reliability, security, and operational efficiency.
Technical Excellence: Set technical standards and best practices across multiple engineering teams.
Mentorship: Provide technical guidance and professional development.
Strategic Transformation: Drive platform modernization using new tools and technologies.
Cross-Functional Collaboration: Partner with technology and business leadership to deliver customer-focused results.
Required Qualifications
Experience: 8+ years of professional software engineering experience, with at least 3+ years in a leadership capacity over high-performance teams.
System Design: Proven track record of delivering and operating large-scale, enterprise-level production systems.
Backend Mastery: Proficiency in building Microservices and Spring Boot, with extensive experience in Java, SOAP, and JSON.
Infrastructure & DevOps: Deep experience with Cloud Foundry and Kubernetes.
SDLC & Tooling: Expertise in the full SDLC, version control, and CI/CD tools (Git, Bitbucket, Jenkins, Maven).
Data & Scripting: Proficiency in Unix tools, shell scripting (Bash, Python, Perl), and database management (SQL queries, PL/SQL, SQL Loader).
Nice to Have: AI & Data Engineering
Experience implementing AI/ML capabilities into production environments, including hands-on experience with AI APIs (OpenAI, Anthropic) and building LLM-powered features (chat, summarization, etc.).
Experience building data pipelines using Google Cloud Platform (GCP) services (DataProc, DBT, PubSub, Kafka, BigQuery, Cloud Spanner).