Company description
Experian is a global data and technology company that drives opportunities for people and businesses around the world. We operate in many markets, such as financial services, healthcare, automotive, agribusiness, insurance, among others. Experian invests in people and in new advanced technologies to unleash the power of data. We have an amazing team of 25,200 employees in 32 countries.
Our uniqueness is valuing yours. Experian's culture, centered on people, inclusive and driven by purpose, is recognized by several awards — including World's Best Workplaces™ 2025 (Fortune Global Top 25) and Great Place To Work™ in 26 countries, among others. Check out Experian Life on social media or explore our careers site to understand why. Experian is also proud to be an employer that promotes equal opportunities and affirmative action.
Job description
We are evolving our BU from a model centered on isolated products to an architecture of platforms and reusable components, which supports critical solutions used by large banks, cooperatives and companies across many segments.
In this context, we are looking for a Specialist Tech Lead to be the technical reference of a software development squad. This person will have autonomy to decide and prioritize the technical implementations that enter the downstream and will be responsible for creating the conditions for the squad to perform: with quality, predictability and autonomy in its own deliveries.
We are looking for an AI Native profile — someone who already uses artificial intelligence in their daily engineering work, applies these techniques in the squad's development cycle and empowers the team to do the same, with real productivity gains and without giving up quality and security.
Main Responsibilities:
- Be the technical reference of the squad and of the demand flow: technical triage, unblocking the team, standards and quality
- Safeguard the technical coherence of what the squad delivers — standards, quality, security and maintainability
- Promote the team's technical autonomy: document, delegate and create criteria so the team can make good decisions without depending on you
- Ensure that local decisions respect the architecture and the platform — or challenge them consciously, with technical rationale
- Provide visibility of technical risks and options to the Tech Manager and PM in advance, before they become problems
- Lead the adoption of AI in the squad: learn, apply and train the team in AI-assisted engineering techniques
- Work on observability and monitoring of services, ensuring minimum instrumentation (logs, metrics and traces) and actionable alerts
- Channel your dissatisfaction with non-performing processes to promote effective changes in the team and in the company
Decisions under your responsibility:
- Technical trade-offs of delivery: architecture, design, standards and technical debt versus speed, always with transparency of impact
- Quality strategy: "done" criteria, testing level, PR gates and definition of acceptable technical risks
- Technical priority of the backlog — hardening, refactors and observability — within the team's capacity
- Minimum standards for observability and reliability: logs, metrics, tracing and hardening priorities
- Incident handling and prevention: root cause analysis, structural actions and executed follow-up
- Adoption of the standards and building blocks defined by the architecture, or proposal of an exception with technical justification and mitigation plan
- Where and how to apply AI in the development cycle, with guardrails for quality, security and intellectual property
What a Day Looks Like:
- Lead technical discussions, guide implementation and raise the engineering standard of the team on a daily basis
- Review PRs focusing on risk, quality and maintainability — and train the team to reduce their dependence on you
- Map technical gaps in the team and drive a practical development plan: mentoring, pairing and learning routines
- Conduct postmortems and map the preventive action plan, with owners and defined deadlines
- Connect the squad's technical needs with partner areas: Product, Infra, SRE, Data and Architecture
- Continuously align risks, technical priorities and team development with the squad's Tech Manager and PM
- Discuss with Architecture decisions with systemic impact (integration, data, security, scalability) and bring operational feedback into the evolution of the platform
- Maintain consistency of standards, integration and reuse together with the other Tech Leads
- Take part in the team's ceremonies and discussions, supporting decision-making and conflict resolution
Expected Results:
- Reduction of incidents originating from deployments and of the recurrence of the same type of failure
- Increased quality: less rework, lower rollback rate and lower bug leakage
- Improved technical health: controlled technical debt, with a plan and continuous execution
- Consistent observability: services with minimum dashboards and alerts and SLOs defined where applicable
- Team evolution: lower dependence on the Tech Lead for day-to-day decisions, with more well-made decisions taken by the group
- Adherence to platform standards: reused building blocks and more predictable integrations
- Measurable productivity gains from the adoption of AI in the development cycle
Qualifications:
- AI Native profile: daily use of AI assistants, skills and agents applied to code, testing and documentation, with the ability to spread these practices across the team
- Experience in Software Architecture: hands-on experience with software development, whether backend, frontend or data
- Proficiency in Programming Languages: Java 17+ with Spring Framework (Spring Boot, Spring Data, Spring Batch) and REST API microservices architecture
- Domain-Driven Design, building reusable components and GenAI applied to products
- Version Control: experience with Git
- Databases: knowledge of relational databases (SQL Server, Oracle, PostgreSQL, MySQL) and non-relational databases (MongoDB)
- Agile Methodologies: solid experience in agile methodologies and technical refinement
- Cloud Architecture: experience with cloud architecture (preferably AWS), including practices of using queues and storage
- Containerization: experience with Docker and Kubernetes
- Unit Testing: experience with JUnit and Mockito
- CI/CD Pipeline: experience with Jenkins
- Monitoring: experience with tools such as Grafana, Kibana and DataDog
- Autonomy and critical thinking: ability to decide under uncertainty, make trade-offs explicit and take ownership of the results of technical decisions
- Desirable: experience in clean architecture
Qualifications
Qualifications
- TechLead
- Java
- SpringBoot
- Microservices
- AWS
- AI Native
Additional information
Serasa Experian is much more than you imagine. With the purpose of creating a better future, expanding opportunities for people and businesses, in Brazil we are more than 4,000 people working in various teams and specialties. Here, every knowledge and diversity complements each other, and you can work on what you love most. We are committed to building an inclusive culture and an environment where people can balance their career with their commitments and personal interests, valuing well-being.
We are very dedicated to being one of the best and most innovative companies to work for in the country, enabling incredible experiences and careers for our people. Our strong people-first approach is recognized externally through several market certifications: we were awarded by Great Place To Work™ in 24 countries and by the international Top Employers certification, in addition to being recognized as one of the best companies for young professionals and having a 4.6 rating on Glassdoor. Each recognition tells us we are on the right path, providing an increasingly better work environment for our talent.
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