We are seeking a highly experienced Technical Manager / Architect with strong hands-on engineering leadership and deep expertise in cloud-native architectures, data-intensive systems, and modern AI-enabled platforms. This role requires end-to-end ownership of solution design and delivery across backend services, data pipelines, and user interface layers, with a strong focus on Financial Crimes, risk analytics, and regulatory compliance domains.
The ideal candidate will combine architectural depth with hands-on engineering capability, driving scalable, secure, and high-performance systems using Java, Python, Spark, GCP, and modern GenAI frameworks.
Key Responsibilities
Technical & Hands-On Leadership
Act as a hands-on Technical Manager, actively contributing to system design, development, code reviews, and architectural decision-making across backend, data, and UI layers.
Lead end-to-end solution delivery from requirements gathering, design, development, testing, deployment, and production support.
Design and oversee cloud-native microservices architectures using Java and Python, integrated with large-scale data processing frameworks such as Apache Spark and GCP data services.
Engineering Excellence & Metrics
Define and enforce engineering quality standards and metrics, including code quality, test coverage, performance SLAs, scalability, reliability, and security benchmarks.
Drive adoption of CI/CD pipelines, DevSecOps practices, automated testing frameworks, and observability tools for high-quality and predictable releases.
Ensure compliance with enterprise architecture standards, data governance policies, and regulatory requirements, particularly for Financial Crimes systems.
Data, GenAI & Analytics Platforms
Lead the design and implementation of enterprise data platforms and operating models supporting Financial Crimes analytics, investigations, risk scoring, and regulatory reporting.
Architect and integrate GenAI solutions (LLMs, RAG architectures, and model orchestration frameworks) into enterprise data ecosystems to enhance detection and investigation capabilities.
Oversee development of large-scale batch and streaming data pipelines using Spark, Python, and GCP-native services to process high-volume transactional and operational data.
UI & Experience Layer
Guide the development of modern ReactJS-based front-end applications for investigator workflows, dashboards, and operational monitoring tools.
Ensure seamless end-to-end integration between UI, APIs, microservices, and data/analytics layers with strong focus on performance and usability.
Stakeholder & Team Leadership
Serve as the primary technical interface between business stakeholders, product owners, compliance teams, and engineering groups.
Mentor and develop senior engineers, fostering a culture of ownership, accountability, and continuous improvement.
Support Agile delivery planning, including estimation, risk management, dependency tracking, and release governance.
Core Competencies
Hands-on Technical Leadership across full-stack systems
End-to-End Solution Ownership and Delivery Accountability
Engineering Metrics, Quality Governance, and DevSecOps Practices
GenAI / LLM Integration and Advanced Analytics Enablement
Cloud-Native Architecture (GCP-focused) and Data Engineering at Scale
