Senior Cloud Software Engineer (AWS/AI)- (full stack)

ECS Tech Inc•Memphis, TN

3h•Hybrid

About The Position

ECS is seeking a Senior Cloud Software Engineer with deep expertise in full-stack development, cloud infrastructure, and AI/ML integration. This role involves designing and deploying intelligent, scalable solutions in AWS environments, with a strong emphasis on modernizing analytical workflows and embedding machine learning capabilities into mission-critical systems. The ideal candidate is a versatile technologist who thrives in fast-paced environments, rapidly adapts to emerging tools and platforms, and consistently delivers innovative, data-driven solutions. You’ll play a key role in transitioning legacy services to the cloud, collaborating with a team of developers and architects to build resilient platforms that support advanced analytics, real-time processing, and intelligent automation. You should be able to apply scientific rigor, business insight, and engineering best practices to solve complex customer challenges. This includes evaluating data accuracy, deploying ML models, and building systems that extract actionable insights. You’re an expert in computer science, engineering, or business, and capable of mentoring others while sharing your cloud and AI/ML expertise across teams and contracts.

Requirements

Proven expertise in full-stack software development, with a strong foundation in Java or C++
Hands-on experience with modern JavaScript frameworks such as React, and proficiency in NodeJS and Java toolchains (NPM, Angular CLI, Maven)
Practical knowledge of deploying and managing applications on AWS using cloud-native methodologies
Solid understanding of core web technologies including HTML, CSS, and JSON
Ability to architect, build, and maintain scalable full-stack applications in cloud and hybrid environments
Experience developing analytical workflows and intelligent data pipelines to support client initiatives
Skilled in designing and implementing responsive user interfaces using popular JavaScript frameworks
Proficient in building secure, production-grade RESTful web services and APIs
Experience deploying and managing distributed messaging systems, particularly Kafka
Capable of monitoring, tuning, and maintaining cloud-based environments for performance and reliability
Strong background in designing systems that collect, store, and process large-scale data for actionable insights, including AI/ML model integration
Comfortable working within agile development teams and contributing to iterative delivery cycles
Master’s Degree in Computer Science, Engineering, Mathematics, Business Management or equivalent.
US Citizen or Green Card Holder (must be eligible to obtain a Public Trust Clearance)
12+ years of general experience in information systems, including at least 8+ years of specialized experience in cloud engineering and full-stack software development
Demonstrated success in collaborating with clients to gather requirements and deliver scalable AI/ML-enabled solutions
Hands-on experience deploying machine learning models and data pipelines in cloud environments (preferably AWS)
Strong understanding of software development lifecycle and agile methodologies, with emphasis on data-driven and intelligent applications

Responsibilities

Lead the design, development, and deployment of full-stack software solutions, including RESTful APIs, modern JavaScript-based user interfaces, and scalable cloud-native architectures
Architect and implement complex analytical workflows and AI/ML pipelines, integrating models into production systems for AWS services
Define and manage data exchange processes between internal and external systems, ensuring secure, high-throughput communication and interoperability
Apply deep expertise in software engineering to troubleshoot and resolve intricate system-level issues, using best practices in performance tuning, testing, and code reviews
Rapidly prototype intelligent applications and analytical tools to support dynamic client initiatives, leveraging infrastructure-as-code and DevOps automation
Evaluate cloud infrastructure and data systems for accuracy, reliability, and cost-efficiency, optimizing deployments across hybrid environments
Communicate complex technical concepts clearly across technical, managerial, and customer audiences, translating requirements into actionable solutions
Research and analyze customer needs to deliver tailored, scalable, and secure cloud applications with embedded machine learning capabilities
Monitor and manage deployed environments, ensuring operational stability, security, and performance
Mentor and train team members, sharing expertise in cloud engineering, software development, and AI/ML integration across organizational boundaries