Software Architect - Java, Cloud & AI

Job Title: Solution Architect - Java, Cloud & AI

Location: Hybrid (Dallas, TX)

Role Overview:

We are seeking an experienced Solution Architect with strong expertise in Java-based enterprise applications, cloud-native architecture, and artificial intelligence solutions. The architect will be responsible for designing scalable, secure, and resilient technology solutions that align with business objectives and enterprise architecture standards.

The ideal candidate will have hands-on experience modernizing legacy applications, building microservices and cloud-native platforms, and integrating AI capabilities such as generative AI, intelligent agents, and retrieval-augmented generation into enterprise applications.

Key Responsibilities

• Design end-to-end solution architectures for complex enterprise applications using Java, Spring Boot, microservices, APIs, and event-driven architecture.
• Define cloud-native architectures using AWS, Azure, or Google Cloud Platform.
• Lead application modernization initiatives, including legacy transformation, containerization, and migration to cloud platforms.
• Design highly available, scalable, secure, and fault-tolerant systems.
• Establish architecture standards, reusable frameworks, design patterns, and engineering best practices.
• Develop architecture diagrams, solution blueprints, integration patterns, data flows, and technical design documents.
• Evaluate and recommend appropriate cloud services, technology platforms, frameworks, and development tools.
• Design and integrate AI-powered capabilities, including generative AI, AI agents, large language models, prompt engineering, and retrieval-augmented generation.
• Architect integrations with enterprise data sources, vector databases, APIs, and machine learning platforms.
• Evaluate AI models based on accuracy, security, scalability, latency, cost, and business requirements.
• Ensure AI solutions comply with responsible AI, data privacy, security, governance, and regulatory standards.
• Collaborate with business stakeholders, product owners, enterprise architects, developers, data engineers, DevOps teams, and cybersecurity teams.
• Provide technical leadership to development teams and conduct architecture, code, security, and performance reviews.
• Identify technical risks, dependencies, architectural gaps, and mitigation strategies.
• Define CI/CD, observability, logging, monitoring, and production support requirements.
• Support technical estimations, proof-of-concept development, vendor evaluations, and technology selection.
• Mentor engineers and promote engineering excellence across delivery teams.

Required Qualifications:

• 10+ years of experience in software engineering, application architecture, or solution architecture.
• 5+ years of experience designing enterprise-scale solutions.
• Strong hands-on experience with Java, Spring Boot, Spring Cloud, REST APIs, and microservices.
• Experience with distributed systems, event-driven architecture, Kafka, messaging platforms, and API gateways.
• Strong experience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform.
• Experience with cloud services involving compute, storage, networking, databases, serverless technologies, security, and monitoring.
• Experience with Docker, Kubernetes, OpenShift, and container orchestration.
• Knowledge of relational databases, NoSQL databases, caching technologies, and data integration patterns.
• Experience designing secure applications using OAuth 2.0, OpenID Connect, JWT, encryption, identity management, and role-based access controls.
• Experience with CI/CD tools and DevOps practices using Jenkins, GitHub Actions, GitLab CI, Azure DevOps, Terraform, or similar technologies.
• Understanding of generative AI, large language models, AI agents, prompt engineering, embeddings, vector databases, and retrieval-augmented generation.
• Experience integrating AI services through platforms or frameworks such as OpenAI, Azure OpenAI, Amazon Bedrock, LangChain, LlamaIndex, or Semantic Kernel.
• Strong understanding of system scalability, performance optimization, resiliency, observability, and disaster recovery.
• Excellent communication, stakeholder management, documentation, and technical leadership skills.

Preferred Qualifications

• Experience with Python and AI application development.
• Experience building enterprise AI assistants, intelligent agents, or knowledge-based applications.
• Familiarity with machine learning operations, model evaluation, model monitoring, and AI governance.
• Experience with Snowflake, Databricks, data lakes, or modern enterprise data platforms.
• Knowledge of financial services, retirement services, wealth management, insurance, or other regulated industries.
• Cloud architecture or AI-related certifications are preferred.