Job description

The Opportunity We are looking for a hands-on Solution Architect to design and guide the building of performant, resilient, and scalable SaaS applications for complex, real-world industrial environments. You will own the architecture of cloud-native, on-premises, microservice-based platforms end-to-end — from data modeling and infrastructure through deployment — while also shaping how emerging AI and agentic technologies are incorporated into our solutions. This is an individual-contributor role with significant technical influence: you will guide engineering teams on architectural decisions, collaborate across product, sales, and customer teams, and remain a hands-on contributor to development. What You'll Do • Solution Architecture: Design and implement performant, resilient, and scalable applications following microservice architecture for both cloud and on-premise deployment. • Technical Leadership: Guide the team on architectural and technical decisions, ensuring adherence to best practices and accepted technical standards. • Cloud & Infrastructure: Architect cloud-native solutions on Azure and/or AWS using containers (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform, Ansible). • On-Premises Deployment: Architect solutions that can be deployed in both cloud and on-premise environments with the same package. • Documentation: Produce detailed architecture diagrams and documentation that accurately capture the current state of applications and new feature implementations. • Data Architecture: Guide data modeling and database design decisions across relational and NoSQL systems (PostgreSQL, MongoDB, SQL Server). • AI & Agentic Enablement: Evaluate and help integrate AI/ML and agentic AI patterns (LLMs, RAG, multi-agent frameworks, knowledge graph) into enterprise solution architectures where they add value. • Cross-Functional Influence: Partner with product management, Corporate Architecture, Platform, sales, customer, and engineering teams to align technical solutions with business needs. • Hands-On Delivery: Actively contribute to development, maintaining high code quality and testing your own work before handoff to QA. • Continuous Learning: Maintain up-to-date knowledge of existing and emerging technologies relevant to the role and communicate risks and issues clearly and in a timely manner. The Technology Stack • Architecture: Microservices, Enterprise Architecture, SaaS design patterns. • AI/ML: LLMs, agentic AI frameworks (LangChain, AutoGen, CrewAI), prompt engineering, retrieval-augmented generation (RAG), vector databases, DeepAgent, Knowledge graph. • Data: PostgreSQL, data platforms/pipelines (e.g., Databricks, Airflow, Delta Lake), OSI PI, PHD. • Cloud & Infrastructure: Azure, AWS, Docker, Kubernetes, Terraform, Ansible. • DevOps: CI/CD build pipelines, GitLab Runner (or equivalent). • Languages: Python, Node.js, Java. • UI: React/Angular (or comparable frontend frameworks), Model Federation. Desired Profile • The Systems Thinker: You see the whole picture — from data layer to infrastructure to user experience — and design architectures that hold up under real-world scale and complexity. • The Pragmatic Builder: You view architecture as a hands-on discipline. You translate designs into working, well-tested code rather than diagrams alone. • The Trusted Advisor: You are comfortable influencing cross-functional stakeholders — product, sales, customer, and engineering — and communicate technical trade-offs clearly. • The Emerging-Tech Evaluator: You stay current on cloud-native/on-premise and AI/agentic patterns and know when — and when not — to apply them to a given problem. Qualifications Must Haves • BS in Computer Science or a related STEM field. • 14+ years of experience in software development or a related technical area. • Proven track record designing and implementing performant, resilient, and scalable SaaS/on-premise applications following microservice architecture for real-world scenarios. • Strong experience with cloud-native technologies (Azure and/or AWS, Docker, Kubernetes, Terraform, Ansible). • Data modeling and database design experience (PostgreSQL, MongoDB, SQL Server). • Experience with data platforms/pipelines (e.g., Databricks, Airflow, Delta Lake, OSI PI, PHD). • Knowledge of AI/ML technologies, including agentic AI frameworks (LangChain, AutoGen, CrewAI), DeepAgent, knowledge graph. • Fluency in one or more of Node.js, Python, Java. • Experience writing unit tests and maintaining high code quality. • Advanced English communication skills. Good to Have • UI experience such as React/Angular. • Oil & Gas domain work experience. • Prior experience building technical or real-time acquisition software in the Oil & Gas industry. • Azure AI Engineer, Azure Data Engineer, or Azure Architect certification.

Requirements

Must-haves

Solution Architecture: Design and implement performant, resilient, and scalable applications following microservice architecture for both cloud and on-premise deployment.
Technical Leadership: Guide the team on architectural and technical decisions, ensuring adherence to best practices and accepted technical standards.
Cloud & Infrastructure: Architect cloud-native solutions on Azure and/or AWS using containers (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform, Ansible).
On-Premises Deployment: Architect solutions that can be deployed in both cloud and on-premise environments with the same package.
Documentation: Produce detailed architecture diagrams and documentation that accurately capture the current state of applications and new feature implementations.
Data Architecture: Guide data modeling and database design decisions across relational and NoSQL systems (PostgreSQL, MongoDB, SQL Server).
AI & Agentic Enablement: Evaluate and help integrate AI/ML and agentic AI patterns (LLMs, RAG, multi-agent frameworks, knowledge graph) into enterprise solution architectures where they add value.
Cross-Functional Influence: Partner with product management, Corporate Architecture, Platform, sales, customer, and engineering teams to align technical solutions with business needs.
Hands-On Delivery: Actively contribute to development, maintaining high code quality and testing your own work before handoff to QA.
Continuous Learning: Maintain up-to-date knowledge of existing and emerging technologies relevant to the role and communicate risks and issues clearly and in a timely manner.
The Technology Stack
Architecture: Microservices, Enterprise Architecture, SaaS design patterns.
AI/ML: LLMs, agentic AI frameworks (LangChain, AutoGen, CrewAI), prompt engineering, retrieval-augmented generation (RAG), vector databases, DeepAgent, Knowledge graph.
Data: PostgreSQL, data platforms/pipelines (e.g., Databricks, Airflow, Delta Lake), OSI PI, PHD.
Cloud & Infrastructure: Azure, AWS, Docker, Kubernetes, Terraform, Ansible.
DevOps: CI/CD build pipelines, GitLab Runner (or equivalent).
Languages: Python, Node.js, Java.
UI: React/Angular (or comparable frontend frameworks), Model Federation.
Desired Profile
The Systems Thinker: You see the whole picture — from data layer to infrastructure to user experience — and design architectures that hold up under real-world scale and complexity.
The Pragmatic Builder: You view architecture as a hands-on discipline. You translate designs into working, well-tested code rather than diagrams alone.
The Trusted Advisor: You are comfortable influencing cross-functional stakeholders — product, sales, customer, and engineering — and communicate technical trade-offs clearly.
The Emerging-Tech Evaluator: You stay current on cloud-native/on-premise and AI/agentic patterns and know when — and when not — to apply them to a given problem.
BS in Computer Science or a related STEM field.

Nice-to-haves

None flagged.

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Keywords to mirror

aiazureawsdockerkubernetessqlmlci/cdpythonnode.jsjavareactangular

Platform: careers-browser
Effort: medium