Staff AI Agent Engineer

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Please note that we will only be able to accept candidates who have the appropriate rights and documentation for employment in India. Who We Are. Axi is a leading global provider of margin and deliverable Foreign Exchange, Contracts for Difference (CFDs), and Financial Spread betting. Our business has evolved into a world-class, multifaceted brokerage with offices in six regions. With heavy investment in the latest trading technology, Axi seeks to offer the most comprehensive end-to-end trading experience available, servicing traders of all levels from beginners to institutional-level clients. Let's talk about the cool stuff you will do at Axi! As a Staff AI Agent Engineer at Axi, you will play a pivotal role in shaping the future of intelligent automation across our Client Experience and Operations functions. You'll design, build, and operate production-grade AI agents that streamline workflows, improve customer experiences, and drive operational efficiency across the business. Working closely with Client Experience, Compliance, Sales, Product, Data, and Engineering teams, you'll transform complex operational challenges into scalable, secure, and measurable agentic solutions. You'll leverage modern AI frameworks, large language models, enterprise integrations, and emerging technologies such as Model Context Protocol (MCP) to build a trusted automation ecosystem that supports critical business functions across onboarding, payments, support operations, trading infrastructure, and data platforms. This is an opportunity to work at the forefront of applied AI within a highly regulated fintech environment while helping shape the next generation of enterprise automation at scale. Your EDGE Assignment/You Will 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. Are you the one? 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. Strong understanding of agentic architectures, tool-calling frameworks, orchestration patterns, and Model Context Protocol (MCP) or similar integration standards. Experience integrating intelligent automation solutions with enterprise systems such as Salesforce, DevRev, customer support platforms, or operational workflow tools. Hands-on experience working with data platforms, data lakes, vector databases, retrieval systems, or distributed data architectures. Strong knowledge of evaluation methodologies, testing strategies, observability practices, and monitoring frameworks for AI-powered systems. Expertise in prompt engineering, model optimization, and managing behavioural changes across evolving foundation models. Experience with modern software engineering practices including Git-based development workflows, CI/CD pipelines, Docker, and cloud-native deployments. Understanding of distributed systems and scalable application architectures. Experience working within regulated industries such as fintech, financial services, banking, trading, or brokerage environments is highly desirable. Knowledge of AI governance, auditability, security controls, privacy requirements, and human-in-the-loop oper

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