Job description: Job Title: Tech Lead Trading Risk & Compliance Systems Department: Technology Services / Market Surveillance Reports To: Head of Regulatory & Digital Experience We are seeking a highly capable and proactive Senior Technical Lead Market Surveillance to drive the successful integration, onboarding, and ongoing operational support of our market surveillance platform. This role is essential in ensuring seamless collaboration with exchanges and trading venues, coordinating data integrations, and managing the performance and change lifecycle of the surveillance solution. You will be the technical focal point between internal teams, the platform vendor, and external counterparties to ensure the platform operates reliably and meets evolving business and regulatory needs. Key Responsibilities: Platform Integration & Exchange Onboarding: Lead technical efforts to integrate new exchanges, venues, and data sources into the surveillance platform, coordinating across vendor, internal infrastructure, and external exchange teams. Facilitate onboarding of new data feeds (e.g., order, trade, drop copy, market data) including format validation, protocol mapping (e.g., FIX), normalization, and certification. Manage and support testing cycles with exchanges and venues, including coordination of system integration testing (SIT), user acceptance testing (UAT), and issue triage. Vendor Coordination & Change Management: Act as the primary technical point of contact with the market surveillance provider, ensuring the vendor delivers against SLAs and functional requirements. Oversee release coordination, environment management (e.g., test, UAT, prod), and feature deployments in partnership with the vendor and internal teams. Drive change request processes, track enhancement requests, and validate rule and configuration changes prior to production deployment. Ensure the SaaS platform continues to meet operational, regulatory, and security expectations. Operational Oversight: Monitor platform availability, data completeness, and alert performance to ensure continuous surveillance coverage. Support incident triage and resolution in collaboration with the SaaS vendor, DevOps, and compliance stakeholders. Establish and maintain dashboards, operational runbooks, and incident response protocols. Drive regular vendor review sessions to review KPIs, issues, and platform roadmap alignment. Cross-Functional Leadership: Partner with Compliance, Surveillance Operations, Legal, and IT Security to ensure surveillance capabilities align with regulatory mandates and internal controls. Represent technical interests in vendor governance meetings, regulatory audits, and internal control assessments. Translate compliance requirements into actionable technical tasks and track their delivery with vendor and internal teams. Required Qualifications: Bachelors degree in computer science, Information Systems, Engineering, or related field. 8+ years of experience in financial services technology, including 3+ years in a technical leadership or systems integration role. Strong understanding of market structure, trade lifecycle, and regulatory surveillance needs across asset classes. Proven experience working with third-party SaaS or managed surveillance platforms and external data providers (e.g., exchanges, brokers). Familiarity with integration protocols such as FIX, SFTP, REST APIs, and data transformation/validation processes. Excellent organizational, communication, and stakeholder management skills. Preferred Skills: Exposure to major market surveillance platforms (e.g., Nasdaq SMARTS, Eventus Validus, Scila, ACA, etc.). Familiarity with regulatory frameworks such as CAT, MAR, MiFID II, and SEC Rule 15c3-5. Experience managing vendor relationships in a regulated environment. Working knowledge of monitoring and observability tools, and cloud/SaaS operations. Note: Must be willing to travel to Dubai.
Position Overview We are seeking an experienced Development Lead to guide and mentor a team of 10-15 engineers at our AI-focused IT company serving clients across all industry sectors. This role combines hands-on technical leadership with people management, focusing on establishing fundamental software engineering practices, scalable architectures, and robust development pipelines for AI applications. A key aspect of this role is working alongside developers who leverage GenAI tools and AI Agents for rapid code generation and automation to establish engineering practices that ensure code quality, maintainability, and scalability. Youll collaborate with the team to build standards and processes that complement AI-assisted development with solid engineering foundations. Key Responsibilities Technical Leadership: Architecture & Design: Lead the design and implementation of scalable, maintainable full-stack applications with AI/ML components Code Quality: Establish and enforce coding standards, design patterns, and best practices across the engineering team Infrastructure: Design and implement robust development, staging, and production environments using cloud platforms (AWS/Azure/GCP) DevOps Excellence: Build and maintain CI/CD pipelines, automated testing frameworks, and deployment strategies Performance & Scaling: Optimize applications for performance, scalability, and cost-effectiveness in production environments Team Development & Mentorship: Engineering Practice Establishment: Work with the team to establish robust software engineering principles, design patterns, and architectural standards that complement AI-assisted development Code Quality Standards: Collaborate with team members to build comprehensive code review processes that ensure maintainability, scalability, and adherence to design principles AI Tool & Agent Integration: Partner with the team to develop effective workflows using GenAI tools and AI Agents while maintaining code understanding and engineering rigor Collaborative Learning: Foster regular technical discussions, architecture reviews, and knowledge sharing sessions to elevate collective understanding Process Development: Work together to establish and refine development practices including Git workflows, testing methodologies, documentation standards, and deployment procedures Engineering Culture: Build a collaborative environment where engineering excellence and rapid AI-assisted development work hand in hand Hands-On Development: Full-Stack Development: Contribute to both frontend and backend development of AI-powered applications AI Integration: Implement and optimize ML/Gen AI features, AI Agents, and integrations Technical Problem Solving: Debug complex issues and provide technical guidance on challenging problems Required Qualifications Experience & Skills: 5-10 years of software development experience with a proven track record of delivering production applications Full-stack expertise with modern web technologies (React/Vue/Angular, Node.js/Python/Java, databases) AI/ML Project Experience: Demonstrated hands-on experience working on AI/ML projects and integrating machine learning models into applications Cloud Platform Proficiency: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) DevOps & Infrastructure: Experience with containerization (Docker/Kubernetes), CI/CD pipelines, and infrastructure as code Architecture Knowledge: Strong understanding of software architecture patterns, microservices, and system design principles Version Control Mastery: Advanced Git skills including branching strategies, code review processes, and automation workflows Leadership & Communication : Technical Leadership: Experience leading technical projects and mentoring other developers Communication Skills: Ability to explain complex technical concepts to team members at various skill levels Problem-Solving: Strong analytical and debugging skills with attention to detail Adaptability: Comfortable working in a fast-paced environment with evolving AI technologies Preferred Qualifications Mobile Development: Experience with iOS/Android development or React Native/Flutter AI/ML Technologies: Hands-on experience with frameworks such as TensorFlow, PyTorch, and Scikit-learn AI Agents: Proven experience building, deploying, and optimizing AI Agents for real-world business use cases Knowledge of vector databases and RAG implementations Experience in MLOps, model deployment, and lifecycle management practices Performance Optimization: Experience optimizing applications for high traffic and large-scale data processing Security Best Practices: Knowledge of secure coding practices and application security Client-facing Experience: Experience working in services/consulting environment with external clients Open Source Contributions: Active participation in open source projects or technical communities What Youll Be Working On Building scalable AI-powered applications for clients across diverse industry sectors Establishing robust development and deployment pipelines for AI/ML and AI Agent applications Creating reusable frameworks and collaboratively developing coding standards for quality development Working with the team to implement comprehensive code review processes and engineering practices Setting up monitoring, logging, and observability solutions for production AI applications Collaborating with client stakeholders and cross-functional teams including data scientists and project managers Exploring and implementing AI Agent-based solutions to enhance client applications Building engineering practices and processes that scale with the teams growth and project complexity Team Environment Youll be leading a team of 10-15 engineers at our Hyderabad office, working on AI solutions for clients across various industries. Many team members are skilled at leveraging GenAI tools and AI Agents for rapid development and are eager to strengthen their software engineering foundations and architectural understanding. This presents an exciting opportunity to work collaboratively with the team to establish engineering practices that balance the speed of AI-assisted development with robust, maintainable code. Youll be working alongside the team to explore AI tools, AI Agents, and emerging technologies while building the engineering culture and standards that will scale with the company’s growth. Growth Opportunities Lead technical initiatives and architectural decisions Expand expertise in emerging AI/ML and AI Agent technologies Develop leadership and mentoring skills Opportunity to shape the technical direction of AI products Conference speaking and technical writing opportunities