Experience:

• 3-5 years of hands-on software engineering experience building production-grade applications using Python and TypeScript
• Proven experience developing, deploying, and operating AI-powered applications, agentic workflows, or large language model solutions in production environments
• Experience integrating intelligent automation solutions with enterprise systems such as Salesforce, DevRev, customer support platforms, or operational workflow tools
• Experience working within regulated industries such as fintech, financial services, banking, trading, or brokerage environments is highly desirable

Responsibilities:

• Design, build, deploy, and continuously optimize production-grade AI agents that automate and enhance operational and customer-facing workflows
• Own the complete agent lifecycle from architecture and prototyping through production deployment, monitoring, and ongoing performance improvements
• Develop clean, maintainable Python and TypeScript solutions that power autonomous decision-making and complex multi-step workflows
• Integrate AI agents with enterprise platforms including CRM systems, ticketing platforms, onboarding systems, payment gateways, trading infrastructure, and Databricks-powered data environments
• Build, maintain, and enhance Model Context Protocol (MCP) servers, custom tools, and integration layers that enable reliable communication between agents and enterprise systems
• Implement robust evaluation frameworks, testing methodologies, observability tooling, audit trails, and governance controls to ensure safe and compliant AI operations
• Design human-in-the-loop workflows, security guardrails, and transparent decision-making processes that align with financial services regulatory requirements
• Collaborate with Client Experience, Compliance, Product, Data Analytics, QA, and Engineering teams to identify automation opportunities and deliver scalable solutions
• Champion AI adoption across the organization by conducting technical demonstrations, workshops, and enablement sessions for business stakeholders
• Continuously evaluate emerging AI models, frameworks, and agentic architectures to drive innovation and improve platform capabilities
• Monitor production systems, identify model drift, optimize performance, and ensure the long-term health and effectiveness of deployed agent solutions

Nice to have:

• Experience working within regulated industries such as fintech, financial services, banking, trading, or brokerage environments

More skills:

Agentic architectures, Tool-calling frameworks, Orchestration patterns, Data platforms, Data lakes, Retrieval systems, Distributed data architectures

Other:

• Competitive compensation package
• Learning and development programs, training resources, and certification support
• 18 days annual leave plus 12 days sick leave
• Local public holidays
• Comprehensive health insurance benefits