Techwave, we are always in an exercise to foster a culture of growth, and inclusivity. We ensure whoever is associated with the brand is being challenged at every step and is provided with all the necessary opportunities to excel in life. People are at the core of everything we do.
Who are we?
Techwave is a leading global IT and engineering services and solutions company revolutionizing digital transformations. We believe in enabling clients to maximize the potential and achieve a greater market with a wide array of technology services, including, but not limited to, Enterprise Resource Planning, Application Development, Analytics, Digital, and the Internet of things (IoT).
Founded in 2004, headquartered in Houston, TX, USA, Techwave leverages its expertise in Digital Transformation, Enterprise Applications, and Engineering Services to enable businesses accelerate their growth.
Plus, we're a team of dreamers and doers who are pushing the boundaries of what's possible.
And we want YOU to be a part of it.
Job Description
Java Solution Architect
Experience: 12+ Years
Employment Type: Full-Time
Role Overview
Seeking an experienced Java Solution Architect to lead enterprise application design and delivery across client engagements. This role blends deep technical expertise with consulting capability, delivery leadership, and the strategic use of modern AI tools to accelerate solutioning, improve quality, and enhance productivity.
The ideal candidate will translate business requirements into scalable, secure, cloud-native architectures while guiding distributed teams and leveraging AI-driven engineering practices.
Key Responsibilities
- Define end-to-end architecture for enterprise-grade Java applications.
- Design microservices, cloud-native, and event-driven solutions.
- Lead client discovery sessions, architecture workshops, and technical discussions.
- Create HLDs, LLDs, architecture diagrams, and reusable reference architectures.
- Provide technical leadership to onshore/offshore teams.
- Ensure adherence to coding standards, governance models, and best practices.
- Support pre-sales activities including solutioning, estimations, and technical proposals.
- Identify architectural risks and drive mitigation strategies.
- Ensure scalability, performance, security, and high availability.
AI-Enabled Engineering & Solutioning
- Leverage AI-assisted development tools (code generation, automated documentation, intelligent test generation, impact analysis) into engineering workflows.
- Use AI platforms and LLM-based tools to accelerate solution design, estimation, prototyping, and modernization assessments.
- Evaluate and recommend AI-driven accelerators for client transformation programs.
- Promote responsible AI usage aligned with security, compliance, and client data policies.
- Contribute to internal AI-enabled reusable frameworks and accelerators.
Technical Expertise Required
- Core Technologies
- Java (8/11/17+), Spring Boot, Spring Cloud
- REST APIs, Microservices Architecture
- Hibernate/JPA
- Messaging systems (Kafka, RabbitMQ)
Cloud & DevOps
- AWS / Azure / GCP
- Docker, Kubernetes
- CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI)
- Infrastructure as Code (Terraform / CloudFormation)
Data & Integration
- RDBMS (PostgreSQL, MySQL, Oracle)
- NoSQL (MongoDB, DynamoDB)
- API management and integration patterns
Security & NFRs
- OAuth2, JWT, SSO
- Performance tuning, high availability, disaster recovery
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science or related field
- 12+ years of software development experience
- 5+ years in architecture roles within services/consulting organizations
- Proven experience in client-facing technical leadership
- Experience delivering large-scale enterprise applications
- Experience with AI-assisted development tools and modern engineering accelerators
Preferred
- Cloud certifications (AWS/Azure/GCP)
- Experience in Healthcare, BFSI, Retail, or Manufacturing domains
- Exposure to modernization, migration, or digital transformation programs
- Experience evaluating AI/ML solution components within enterprise ecosystems
Key Competencies
- Client-focused and outcome-driven mindset
- Strong communication and executive presentation skills
- Delivery ownership and accountability
- Ability to lead distributed and cross-functional teams
- Innovation-oriented approach with AI adoption mindset
