AWS Cloud Engineer

Incedo•Austin, TX

About The Position

As a Principle Engineer - AWS Python at Incedo, you will be responsible for developing and maintaining applications on the Amazon Web Services (AWS) platform. You will be expected to have a strong understanding of Python and AWS technologies, including EC2, S3, RDS, and Lambda. Guide development teams through best practices, design patterns, and coding standards while ensuring high-quality, maintainable, and secure code. Collaborate with business teams, product owners, and stakeholders to convert functional requirements into detailed technical designs and implementation plans. Lead the design and deployment of AI and cloud-native solutions using AI LLMs, inbuild agents including AWS services, ensuring scalability, cost optimization, and operational efficiency. Identify bottlenecks and implement performance tuning strategies, ensuring systems remain reliable and responsive under high load. Lead regular code reviews and architecture discussions to enforce consistency, quality, and alignment with enterprise standards. Lead the estimation, planning, and delivery of application and tool development efforts, providing accurate timelines, resource allocation, and risk assessments. Collaborate closely with cross-functional teams including product management, DevOps, and QA to align technical implementation with business requirements. Drive continuous architectural improvement initiatives by defining and evolving system architecture and integration patterns, promoting best practices in microservices, APIs, event-driven design, and cloud-native solutions. Leverage AI-driven agents within container orchestration platforms (e.g., Kubernetes) to automate deployment, scaling, monitoring, and management of complex applications, enhancing system resilience, efficiency, and self-healing capabilities. Evaluate and Optimize architecture and performance across applications wherever applicable. Provide strategic technical direction and vision by evolving the enterprise technical reference model and defining comprehensive technology and architecture roadmaps across Cetera’s applications and tools to support modernization and digital transformation initiatives.

Requirements

14+ years of hands-on experience in software development with a track record of guiding technical teams.
Deep knowledge of core JAVA programming languages, modern frameworks, cloud infrastructure, and software design patterns.
AWS Cloud knowledge is must, services like S3, Lambda, Event bridge & API Gateway, Java Spring boot & Python.
Strong ability to communicate complex technical concepts clearly, delegate effectively, and resolve team conflicts.
Exceptional analytical and troubleshooting skills to navigate technical roadblocks and manage project risks.
Excellent understanding of AI Native delivery model across the SDLC with hands on experience.

Nice To Haves

Willing to learn and lead the team along the journey.
11-12 years of work experience in relevant field
B.Tech/B.E/M.Tech or MCA degree from a reputed university.
Computer science background is preferred

Responsibilities

Developing and maintaining applications on the Amazon Web Services (AWS) platform.
Guiding development teams through best practices, design patterns, and coding standards.
Collaborating with business teams, product owners, and stakeholders to convert functional requirements into detailed technical designs and implementation plans.
Leading the design and deployment of AI and cloud-native solutions using AI LLMs, inbuild agents including AWS services.
Identifying bottlenecks and implementing performance tuning strategies.
Leading regular code reviews and architecture discussions.
Leading the estimation, planning, and delivery of application and tool development efforts.
Collaborating closely with cross-functional teams including product management, DevOps, and QA.
Driving continuous architectural improvement initiatives by defining and evolving system architecture and integration patterns.
Leveraging AI-driven agents within container orchestration platforms (e.g., Kubernetes) to automate deployment, scaling, monitoring, and management of complex applications.
Evaluating and optimizing architecture and performance across applications.
Providing strategic technical direction and vision by evolving the enterprise technical reference model and defining comprehensive technology and architecture roadmaps.