Senior Software Engineer (JAVA)

Behavox

4h • Hybrid

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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed
• Number of Employees: 101-250 employees