Preferred Skills
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
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Category
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Requirements
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Backend
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Java 11+, Spring Boot, Microservices architecture, REST APIs, JPA/Hibernate
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Frontend
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Angular (modern versions), TypeScript; React experience a plus
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Databases
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MSSQL, MySQL, MongoDB; query optimization; schema design
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Search & Messaging
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Search engines (Solr/Elasticsearch); Message queues (ActiveMQ, Kafka, or similar)
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Data Processing
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ETL pipelines; batch processing; job scheduling frameworks
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Cloud & Infrastructure
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GCP or AWS; Kubernetes; containerization; CI/CD pipelines
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DevOps & Tools
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Azure DevOps; Terraform or similar IaC; JIRA; Confluence
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Security
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SSO/OAuth/SAML; Identity providers (Okta or similar); PCI-DSS compliance
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Architecture
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Distributed systems design; API design; system integration patterns
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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. You will be expected to:
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:
1. Updated resume highlighting relevant experience
2. Brief summary of your largest technical leadership engagement
3. Examples of architectural decisions you’ve driven
4. Current and expected compensation
