This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Technology Solutions Architect Lead based in United States.
This leadership role drives the delivery of complex digital, data, AI, and cloud modernization programs across enterprise environments.
You will combine solution architecture expertise with strong delivery ownership, coordinating multiple teams, vendors, and technical workstreams.
The role focuses on building scalable cloud-native systems across commerce, operations, engineering, and enterprise platforms.
You will guide teams working with microservices, event-driven architectures, Kubernetes, Java, AWS, Azure, data platforms, and AI-enabled technologies.
Beyond architecture, you will establish delivery standards, manage milestones and risks, and ensure solutions reach production reliably and securely.
You will also mentor engineers, strengthen DevSecOps practices, and introduce AI-assisted engineering capabilities into delivery workflows.
This is a high-impact opportunity to influence technical strategy while remaining closely involved in execution, quality, and stakeholder alignment.
Accountabilities:
- Lead architectural design and delivery of complex projects across CPQ, digital commerce, cloud, data, and AI environments, including integrations with multiple vendors and emerging technologies.
- Own end-to-end execution of complex, multi-team programs, establishing delivery plans, milestones, dependencies, risks, and release objectives.
- Lead sprint planning, backlog refinement, release readiness, and other Agile delivery activities to maintain predictable execution.
- Provide technical oversight across architecture, development, coding, testing, deployment, and production delivery.
- Guide engineering teams working with Java, Spring Boot, Kubernetes, Docker, Kafka, AWS, PostgreSQL, Redis, and distributed systems.
- Define architecture documentation standards and communicate designs through established modeling practices such as C4 models.
- Translate architectural designs into actionable workstreams with clear dependencies, technical priorities, and delivery expectations.
- Maintain high standards for code quality, reliability, scalability, security, and performance through technical reviews and coaching.
- Establish and reinforce testing, CI/CD, observability, and DevSecOps practices using tools such as SonarQube, Snyk, Datadog, CloudWatch, and automated testing frameworks.
- Support smooth production releases, post-launch stabilization, incident resolution, and root-cause analysis.
- Mentor engineers, encourage accountability, support onboarding and knowledge sharing, and promote continuous engineering improvement.
- Partner with Product, Architecture, Security, Data, and other stakeholders to align priorities, communicate progress, and resolve blockers.
- Drive adoption of AI coding assistants and GenAI engineering platforms, incorporating AI-enabled quality, documentation, and automation practices into development workflows.
Requirements:
- 8–12+ years of experience in engineering, solution architecture, or technical delivery leadership.
- Proven experience delivering distributed, event-driven, cloud-native, and highly scalable systems.
- Strong knowledge of Agile and Scrum methodologies combined with expertise in AWS and Azure cloud architecture.
- Deep understanding of distributed systems, microservices, Domain-Driven Design, event-driven architecture, and technologies such as Kafka, Event Hubs, and Service Bus.
- Strong knowledge of software architecture and design patterns, including MVC and related enterprise application patterns.
- Advanced expertise in cloud computing and containerization using Docker and Kubernetes across AWS and Azure environments.
- Strong experience with Java and Spring Boot, Kubernetes, Docker, AWS services such as EventBridge, SQS, Lambda, and RDS, Kafka and streaming technologies, CI/CD, and monitoring.
- Experience with DevOps practices, infrastructure as code, and CI/CD pipelines; ARM templates, Bicep, Go, Ansible, and Python are advantageous.
- Experience delivering ML/AI solutions or data pipelines is a plus.
- Experience with GenAI enablement platforms or AI coding assistants is preferred.
- Familiarity with GraphQL/Hasura, FastAPI, Redis, Spark, Airflow, or SageMaker is beneficial.
- Understanding of security, data privacy, enterprise governance, and operational requirements for large-scale systems.
- Excellent communication, planning, stakeholder management, and technical leadership skills.
- Ability to translate complex architectural concepts into clear delivery plans and actionable technical workstreams.
Benefits:
- Opportunity to lead high-impact modernization programs spanning cloud, commerce, data, AI, and enterprise technology.
- High level of technical ownership across architecture, delivery, engineering standards, and emerging technology adoption.
- Collaboration with multidisciplinary teams across Product, Architecture, Security, Data, and Engineering.
- Opportunity to mentor engineers and influence engineering culture and delivery practices.
- Exposure to cloud-native, distributed, AI-enhanced, and event-driven technologies at enterprise scale.
- Opportunity to work with emerging GenAI engineering tools and AI-assisted development practices.
- Remote U.S. position with the opportunity to contribute to large-scale technology transformation initiatives.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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