Posted:21 hours ago|
Platform:
On-site
Full Time
Define and establish the overall technical architecture, leading design discussions to ensure the development of scalable, secure, and high-performance applications.
Provide hands-on technical expertise and guidance across the complete technology stack to ensure architectural consistency and engineering excellence.
Design and implement enterprise-grade solutions utilizing Python, Java, and Node.js ecosystems.
Architect and manage event-driven systems and messaging architectures using Kafka or equivalent platforms.
Design, oversee, and optimize data pipelines and data engineering workflows to support analytical and operational requirements.
Collaborate with stakeholders, product managers, and cross-functional teams to translate business objectives into well-defined technical solutions.
Drive the adoption of cloud-native architectures, microservices, and other modern software engineering practices.
Design, implement, and maintain CI/CD pipelines, infrastructure automation, and application monitoring systems to support continuous delivery and operational excellence.
Conduct code reviews, design reviews, and technical audits to ensure adherence to established standards and best practices.
Evaluate, design, and integrate AI/ML and LLM-based capabilities into existing and new architectures to enhance system intelligence and automation.
Provide technical mentorship and leadership, fostering a culture of innovation, accountability, and continuous improvement across engineering teams.
Continuously assess emerging technologies, frameworks, and methodologies to recommend strategic improvements and ensure architectural relevance.
Oversee technical risk identification and mitigation, ensuring alignment of all architectural decisions with project timelines, quality benchmarks, and organizational objectives.
Key Skills:
Backend: Java (Spring Boot, Microservices, REST APIs), Python (Django, Fast API, Flask), Node.js (Express)
Frontend: React, Angular, with JavaScript/TypeScript skills.
Data Engineering: ETL/ELT pipelines, data warehousing, streaming architectures (Kafka, Spark).
Cloud & DevOps: AWS, Azure, GCP, Docker, Kubernetes, CI/CD, Infrastructure-as-Code.
Databases & Messaging: PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch; event-driven architectures and message queuing.
· Skills: System design, architecture patterns, distributed systems, scalability, performance, and security.
Leadership: Team mentoring, Agile/Scrum experience, strong communication and collaboration skills.
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