- Location
- Noida, UP,IN, IN
- Type
- Full-time
- Department
- Engineering
- Seniority
- Senior
- Experience
- 10+ years
- Education
- Master
- Source
- Eightfold
Description
Hands-on Software Engineering Design, develop, test, and maintain high-quality backend services, APIs, distributed components, and cloud-native capabilities for the Ready product. Write clean, maintainable, performant, and well-tested code using Java and modern enterprise engineering practices. Take ownership of complex technical deliverables from design through implementation, testing, release, and production support. Contribute to code reviews, design reviews, and engineering discussions with a focus on quality, simplicity, scalability, and maintainability. Quickly learn and apply new technologies, frameworks, tools, and platform capabilities as product and engineering needs evolve. Technology Stack & Technical Roadmap Contribute to the evaluation, selection, and evolution of the technology stack for the Ready product, including application frameworks, database technologies, messaging, caching, observability, and cloud-native services. Partner with architects and engineering leaders to shape a practical technical roadmap that improves scalability, reliability, performance, developer productivity, and customer experience. Bring strong technical judgment to build-versus-buy decisions, framework selection, modernization efforts, and platform evolution. Help translate product and business needs into sustainable technical designs and implementation plans. Architecture & Design Design scalable and resilient software components that align with enterprise SaaS architecture principles. Contribute to architecture discussions for distributed systems, microservices, APIs, event-driven workflows, data-intensive features, and integration patterns. Identify design risks early and recommend pragmatic solutions that reduce complexity while supporting long-term product growth. Document technical designs, trade-offs, assumptions, and implementation approaches clearly for engineering teams. Observability, Troubleshooting & Operational Excellence Use observability platforms, logs, metrics, traces, dashboards, and alerts to understand system behavior and diagnose production issues. Troubleshoot complex technical problems across application, database, infrastructure, integration, and deployment layers. Contribute to root-cause analysis, incident follow-ups, and reliability improvements that prevent recurring issues. Improve monitoring, telemetry, logging, and service health practices using tools such as OpenTelemetry, Grafana, Prometheus, Kibana, Datadog, Splunk, or similar platforms. Support operational readiness through automation, meaningful alerts, clear runbooks, and production-aware engineering practices. Performance Engineering & Database Technology Tune application and database performance, including query optimization, indexing, connection management, caching, concurrency, transaction handling, and service-level latency improvements. Analyze performance bottlenecks using profiling, load testing, benchmarking, database execution plans, and production telemetry. Design reliable and scalable data models using relational database technologies and appropriate data access patterns. Collaborate with teams to improve throughput, latency, resiliency, cost efficiency, and scalability of product services. AI-First Engineering & Agents Apply AI-assisted development tools to improve software design, coding, testing, documentation, troubleshooting, and developer productivity. Bring practical understanding of AI trends, agents, coding assistants, and intelligent automation into engineering discussions. Identify opportunities where AI and agents can improve engineering workflows, support diagnostics, automate repetitive tasks, or enhance product capabilities. Follow responsible AI practices with attention to security, privacy, quality, reliability, and governance. Technical Collaboration & Mentorship Collaborate closely with engineers, architects, product managers, quality engineers, SRE, and engineering leaders to deliver reliable product capabilities. Lead focused technical discussions when needed, especially around design choices, implementation approaches, troubleshooting, and performance improvements. Mentor engineers through code reviews, design feedback, debugging support, and sharing of engineering best practices. Influence team-level engineering quality through strong hands-on contribution, technical credibility, and practical guidance. Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. 10+ years of professional software engineering experience, including experience building enterprise-scale software products. Strong hands-on proficiency in Java, backend service development, object-oriented design, concurrency, performance tuning, and modern Java frameworks. Strong experience with database technologies, SQL, schema design, indexing, query optimization, transaction management, and database performance troubleshooting. Experience designing and developing distributed systems, microservices, REST APIs, event-driven components, and cloud-native applications. Hands-on experience with cloud platforms such as AWS, Azure, or GCP. Strong understanding of observability, monitoring, logging, tracing, metrics, alerting, and production diagnostics. Experience troubleshooting complex technical issues across application, database, infrastructure, and integration layers. Strong understanding of performance engineering, including profiling, load testing, caching, query tuning, and scalability analysis. Ability to learn new technologies quickly and apply them effectively in production-grade software development. Practical understanding of AI-assisted engineering tools, AI agents, and emerging automation capabilities. Experience working on large-scale enterprise SaaS products serving global customers. Experience contributing to technical roadmaps, platform modernization, cloud transformation, or technology stack evolution. Experience with Kubernetes, containers, CI/CD pipelines, DevOps practices, and Infrastructure as Code. Hands-on experience with observability tools such as OpenTelemetry, Grafana, Prometheus, Kibana, Splunk, Datadog, or similar platforms. Experience with distributed caching, messaging platforms, asynchronous processing, and event-driven architecture. Strong understanding of secure software development, authentication, authorization, data protection, and enterprise integration patterns. Experience using AI coding assistants, engineering agents, intelligent automation, or AI-enabled operational tooling. Demonstrated ability to mentor engineers while remaining deeply hands-on in design, coding, debugging, and delivery. Key Attributes Strong hands-on developer who is ready to write code and solve hard technical problems. Fast learner who can evaluate and adopt new technologies pragmatically. Production-minded engineer with strong focus on reliability, observability, scalability, performance, and security. Practical technical leader who influences through code quality, engineering judgment, and collaboration. Comfortable troubleshooting deep technical issues and driving them to resolution. Curious and forward-looking engineer with strong interest in AI-first development and agent-based automation
