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. 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:
o Documentation: System docs, API specs, runbooks, and knowledge base articles
o Implementation: Feature development, bug fixes, refactoring, and code generation
o Code Reviews: AI-assisted review workflows that catch issues early
o Testing: Test case generation, test data creation, and coverage analysis
o 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
