Technical Architect/Development Lead

Cloud Backend Developer

Pay Range: $68hr - $71hr

Lead the design and development of scalable, resilient, and cloud-native backend systems. Combine architectural vision with hands-on development to deliver high-quality solutions. Drive end-to-end implementation from concept to production in a client-facing environment.

Requirements/Must Have:

• 10–14 years of overall software development experience.
• 4+ years of experience in technical lead or architect roles.
• Strong hands-on experience in Python for backend development.
• Experience in Java, particularly with Spring Boot and microservices.
• Proven expertise in solution architecture and distributed system design.
• Extensive experience with AWS cloud services such as EC2, S3, Lambda, RDS, and EKS.
• Strong understanding of microservices and distributed architectures.
• Hands-on experience with Docker and Kubernetes.
• Experience with logging, monitoring, and observability tools such as Kibana and ELK.
• Experience implementing CI/CD pipelines and DevOps practices.
• Strong understanding of data structures, scalability, and performance tuning.
• Excellent communication and client-facing skills.
• Experience leading senior engineers and influencing architectural decisions.
• Ability to work effectively with geographically distributed teams.

Responsibilities:

• Lead end-to-end solution architecture and system design for cloud-native applications.
• Drive hands-on development using Python and Java for backend services and microservices.
• Architect and implement solutions on cloud platforms.
• Design and build scalable, resilient, and secure distributed systems.
• Lead and mentor development teams, enforcing coding standards and best practices.
• Collaborate with clients and stakeholders for requirements analysis and solution design.
• Design and implement containerized solutions using Docker and Kubernetes.
• Define and implement CI/CD pipelines and DevOps best practices.
• Ensure system observability, logging, and monitoring.
• Drive performance optimization, reliability, and scalability initiatives.

Should Have:

• Experience with AI/ML technologies.
• Exposure to big data technologies such as Spark and Kafka.
• Experience with API gateways and event-driven architecture.
• Knowledge of security best practices in cloud environments.

Skills:

• Proficiency in Python and Java.
• Strong knowledge of microservices and distributed systems.
• Expertise in cloud platforms and containerization technologies.
• Strong leadership, problem-solving, and analytical skills.
• Excellent communication and collaboration abilities.