Senior Software Engineer (JAVA)
About The Position
The Software Engineer (Java) operates at a senior engineer level, driving technical direction across core product domains. The role combines deep hands-on Java engineering with architectural ownership — from high-level system design and technology selection to leading delivery of critical, cross-cutting platform capabilities. At this level, engineering excellence extends beyond implementation: the engineer determines the right approach to complex problems, communicates technical decisions across functions, participates in hiring, and is accountable for the long-term health of the systems they own. This level demands sound judgment on technology and business trade-offs and the ability to act as a technical lead. A defining expectation is mastery of AI-assisted engineering — leveraging agentic AI tools as force multipliers while retaining full ownership of architecture, quality, and technical outcomes.
Requirements
- Expert Java engineering: Deep understanding of Java internals — GC tuning, Collections Framework, advanced concurrency (java.util.concurrent, multithreading), NIO/NIO2, performance profiling, and heap-dump analysis.
- Mastery of Spring Framework (IoC/DI, bean lifecycle, Spring Boot).
- SOLID principles, Clean Code practices, and GoF design patterns.
- Software architecture and design patterns: Expertise in monolith and microservices architectural styles — including migration patterns and domain-driven decomposition.
- Inter-process communication design (REST, gRPC, messaging), transaction management in distributed systems (Sagas, 2PC), CQRS, Event Sourcing, and external API design focused on scalability, security, and documentation.
- Cloud-native platforms and infrastructure: Experience designing high-availability and high-load systems on GCP (preferred), AWS, and Azure.
- Cloud security best practices: IAM, VPC, data encryption, JWT/JWS/JWE.
- Infrastructure as Code (Terraform or equivalent) and Twelve-Factor App methodology.
- Observability, reliability and deployment: Implementing full observability stacks: structured logging, distributed tracing, metrics, and alerting.
- SLI/SLO/SLA frameworks.
- Deployment strategies: Rolling Updates, Blue/Green Deployments, Canary Releases.
- AI-assisted engineering: Practitioner-level command of agentic AI tools applied to software engineering — encompassing prompt engineering techniques, AI context management and its limitations, sub-agents, skills and plugins, multi-agent orchestration, and team-of-agents architectures.
- Experience with Claude Code (Anthropic), Codex (OpenAI), or equivalent is mandatory.
Responsibilities
- Lead high-level design for complex, cross-service features.
- Evaluate and select appropriate technologies, frameworks, and architectural patterns before delegating implementation.
- Produce and maintain architecture documentation: design docs, ADRs, tech specs, and wiki pages.
- Own and implement critical product components — including prototyping, architecture validation, and production-grade code.
- Ensure correctness, performance, and long-term maintainability with comprehensive test coverage (unit, integration, contract, component).
- Drive the engineering agenda for assigned product areas.
- Proactively identify gaps in requirements, architectural limitations, and technical risks.
- Contribute to product roadmap planning and delivery estimation.
- Participate in hiring processes.
- Drive technical communication across engineering, product, DevOps, and ML teams.
- Communicate technical decisions clearly to non-technical stakeholders.
- Produce design documents and participate in tech talks and knowledge-sharing sessions.
- Direct agentic AI tools (Claude Code, Codex, or equivalent) across the full engineering workflow — code generation, testing, refactoring, debugging, and documentation.
- Demonstrated ability to apply advanced prompt engineering, manage AI context limitations, compose multi-agent orchestration workflows, and critically evaluate AI-generated outputs for correctness, security, and quality.
- Ability to establish guardrails and improve agent configurations to raise the quality bar.
- AI proficiency amplifies — it does not replace — deep engineering judgment and technical accountability.
Benefits
- Competitive cash compensation
- Equity award aligned with long-term value creation
- Comprehensive health insurance for employees and their families
- Generous time-off policy of 30 days annually, plus public holidays and sick leave
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
Number of Employees
101-250 employees
