Technical Architect / Project Lead - Java/J2EE
Position Overview
We are seeking an experienced Java Technical Architect / Project Lead to join our engineering team supporting a large-scale FinTech platform. This is a dual role combining technical architecture ownership with project leadership responsibilities.
You will be the technical authority for the team while also being hands-on with individual development tasks. This role is ideal for someone who thrives in both strategic architecture discussions and tactical implementation work - not just overseeing from a distance, but actively contributing to the codebase while guiding the team.
Required Qualifications
Experience
12+ years of software engineering experience with progressive responsibility 4+ years in a Technical Lead, Architect, or Engineering Manager role Proven experience leading offshore/distributed engineering teams Track record of delivering large-scale enterprise applications Experience in FinTech, payments, or e-commerce domains preferred Background working with US-based enterprise clients
Technical Skills
Category
Requirements
Backend
Java 11+, Spring Boot, Microservices architecture, REST APIs, JPA/Hibernate
Frontend
Angular (modern versions), TypeScript; React experience a plus
Databases
MSSQL, MySQL, MongoDB; query optimization; schema design
Search & Messaging
Search engines (Solr/Elasticsearch); Message queues (ActiveMQ, Kafka, or similar)
Data Processing
ETL pipelines; batch processing; job scheduling frameworks
Cloud & Infrastructure
GCP or AWS; Kubernetes; containerization; CI/CD pipelines
DevOps & Tools
Azure DevOps; Terraform or similar IaC; JIRA; Confluence
Security
SSO/OAuth/SAML; Identity providers (Okta or similar); PCI-DSS compliance
Architecture
Distributed systems design; API design; system integration patterns
Leadership Skills
Experience managing teams of 10-15 engineers Ability to balance hands-on work with leadership responsibilities Strong written and verbal communication in English Experience with Agile/Scrum methodologies Track record of mentoring and developing engineers
AI & Productivity Skills
Active user of AI-assisted development tools (Claude, Copilot, Cursor, or similar) Demonstrated ability to leverage AI for code generation, documentation, and problem-solving Experience introducing AI tools and practices to engineering teams Understanding of when AI assistance is appropriate and its limitations
Preferred Qualifications
Experience with legacy system modernization and migration projects Knowledge of loyalty programs, rewards, or payment processing systems Familiarity with AngularJS (legacy) codebases Experience with BigQuery or similar data warehousing solutions Understanding of PCI-DSS compliance requirements
Platform Context
You will be working on a complex enterprise platform with:
Multiple interconnected systems and services Mix of legacy and modern technology stacks High availability and zero-downtime deployment requirements Enterprise integrations with major financial and retail brands Significant transaction volumes requiring performance optimization
AI-Driven Engineering Excellence
A critical aspect of this role is championing AI-assisted development across the team.
Maximize AI Adoption
Leverage AI tools (Claude, Copilot, Cursor, etc.) extensively in your own workflow as a model for the team Identify high-impact opportunities where AI can accelerate development, improve quality, and reduce toil Stay current with the latest AI tools, techniques, and best practices adopted by cutting-edge engineering teams Evaluate and introduce new AI capabilities as they emerge
Guide Team AI Practices
Train and mentor team members on effective AI usage for their specific roles Develop guidelines, prompts, and playbooks for common tasks: Documentation: System docs, API specs, runbooks, and knowledge base articles Implementation: Feature development, bug fixes, refactoring, and code generation Code Reviews: AI-assisted review workflows that catch issues early Testing: Test case generation, test data creation, and coverage analysis Processes: Sprint planning, ticket refinement, incident analysis, and retrospectives
Build AI Infrastructure
Develop harnesses, templates, and tooling that make AI adoption frictionless for the team Create project-specific context and documentation that maximizes AI effectiveness Establish feedback loops to continuously improve AI-assisted workflows Build reusable prompts and patterns for recurring engineering tasks
Evolve Processes Continuously
Regularly assess and update team processes to incorporate AI advancements Measure productivity gains and identify areas for further optimization Share learnings and best practices across the organization Drive a culture of experimentation and continuous improvement
Balance Automation with Judgement
Establish appropriate human review checkpoints for AI-generated outputs Define clear boundaries for when AI assistance is appropriate vs. when human expertise is required Ensure AI usage aligns with security, compliance, and quality standards Maintain team skills and understanding - AI augments, not replaces, engineering expertise The goal is to maximize productivity, increase development velocity, and minimize errors - while maintaining the human oversight and judgement essential for enterprise-quality software.
Soft Skills
Technical Communication: Explain complex concepts clearly to both technical and non-technical audiences Decision Making: Make sound technical decisions with incomplete information Ownership: Take end-to-end accountability for team deliverables Adaptability: Navigate ambiguity in a fast-paced enterprise environment Collaboration: Work effectively across time zones and organizational boundaries Continuous Learning: Stay current with emerging technologies and practices
About the Engagement
This position is with DeviceDriven, a technology consulting firm partnering with a leading US-based FinTech company. The platform serves major financial institutions and enterprise clients with mission-critical services.
We offer:
Long-term engagement with growth opportunities Exposure to enterprise-scale technical challenges Collaboration with experienced US engineering teams Opportunity to shape technical direction and team culture
Application Process
Interested candidates should provide:
Updated resume highlighting relevant experience Brief summary of your largest technical leadership engagement Examples of architectural decisions you’ve driven Current and expected compensation
