Senior Software Engineer

Responsibilities:

• Develop, implement, and maintain software components, APIs, and user interfaces with clean, efficient, and reliable code.
• Collaborate with cross-functional teams to design scalable, secure, and maintainable solutions aligned with business requirements.
• Participate in project discovery and translate technical requirements into detailed designs and functional logic.
• Drive full software development lifecycle activities, including continuous integration, automated testing, deployment, and monitoring.
• Integrate AI/ML components and leverage advanced tools to enhance development efficiency and innovation.
• Provide technical guidance to small engineering teams and support knowledge sharing.
• Monitor application performance and ensure adherence to project timelines and quality standards.
• Lead architectural design discussions and drive decisions on technology selection, system decomposition, and integration patterns.
• Design and implement event-driven, microservices, and serverless architectures for high-availability systems.
• Champion engineering best practices, including code reviews, testing strategies, CI/CD optimization, and technical debt management.
• Evaluate and adopt emerging technologies, frameworks, and AI-powered tools to improve team productivity and solution quality.
• Collaborate with product and business stakeholders to align technical solutions with strategic objectives.

Requirements:

• Proficiency in software development using languages such as JavaScript, TypeScript, Python, Java, Rust, Dart, Go, Kotlin, or C++.
• 6+ years of experience with the full software development lifecycle, including embedded software development, continuous integration, automated testing, and deployment.
• Strong understanding of software architecture, platform design, and cloud engineering principles.
• Ability to translate business requirements into scalable, secure, and maintainable technical solutions.
• Familiarity with Agile methodologies and version control systems.
• Demonstrated skills in collaboration, technical leadership, and effective communication with cross-functional teams.
• Experience designing and operating distributed systems, microservices, and cloud-native applications at scale.
• Deep knowledge of at least one cloud platform (AWS, Azure, or GCP), including compute, storage, networking, and managed AI/ML services.
• Experience with container orchestration (Kubernetes, ECS), service mesh, and infrastructure-as-code (Terraform, Pulumi).
• Proven ability to mentor engineers, lead design reviews, and influence technical direction.
• Strong understanding of security engineering practices, performance optimization, and observability.

Preferred Qualifications:

• Experience building applications that integrate LLM APIs, RAG pipelines, or agentic AI components.
• Familiarity with MCP (Model Context Protocol) or tool-layer integrations for AI-driven systems.
• Experience with real-time systems, streaming architectures (Kafka, Flink, Kinesis), and event sourcing patterns.
• Knowledge of WebAssembly (WASM), edge computing, or progressive web application (PWA) patterns.
• Experience with database scaling strategies, including sharding, replication, and multi-region deployments.
• Contributions to open-source projects or technical community leadership.
• Familiarity with AI governance, responsible AI practices, and data privacy regulations (GDPR, CCPA, SOC2).