AI Architect – Enterprise Java& GenAI & AI-Powered Engineering - 26-13312
- Full-time
AI Architect – Enterprise Java, GenAI & AI-Powered Engineering
Location: Plano, TX
Experience: 12–15 Years
AI/GenAI Experience: 2–3+ Years of Hands-On Experience
Work Model: Hybrid – 3 Days/Week Onsite
Employment Type: 12 Months
Role Overview
We are seeking a highly experienced AI Architect with strong expertise in Enterprise Java, Generative AI (GenAI), Agentic AI, and AI-powered software engineering.
The ideal candidate will combine deep expertise in Java enterprise architecture with hands-on experience in LLMs, RAG, AI Agents, and GenAI frameworks. The candidate should also have practical experience using AI-powered development tools such as Windsurf, Cursor, GitHub Copilot, Claude Code, OpenAI Codex, or equivalent agentic IDEs.
This role requires close collaboration with customers, business stakeholders, architects, and engineering teams to drive AI-led transformation initiatives. The candidate will participate in customer workshops, architecture discussions, solution design, PoCs, technical reviews, and team mentoring.
Key Responsibilities AI & GenAI Architecture
- Design and implement enterprise-scale GenAI, RAG, and Agentic AI solutions.
- Lead engagements from discovery and architecture through PoC, MVP, and production rollout.
- Evaluate LLMs, AI frameworks, vector databases, and cloud AI services.
- Integrate AI capabilities into enterprise applications and business processes.
Enterprise Java Architecture
- Provide technical leadership for Java, Spring Boot, REST APIs, Microservices, and event-driven architectures.
- Support modernization of legacy applications using cloud-native and AI-assisted approaches.
- Review code and establish architecture and engineering standards.
- Guide engineering teams on scalable and maintainable application design.
AI-Powered Engineering
- Demonstrate practical use of AI development tools, including:
- Windsurf
- Cursor
- GitHub Copilot
- Claude Code
- OpenAI Codex
- Equivalent AI-powered/Agentic IDEs
- Drive AI adoption across the SDLC, including requirements, development, testing, code review, documentation, and modernization.
- Measure and improve engineering productivity through AI-enabled development practices.
Customer Engagement
- Conduct customer workshops, discovery sessions, and architecture discussions.
- Translate business requirements into scalable AI and technology solutions.
- Support proposals, solutioning, estimations, and executive presentations.
- Work closely with customer teams, architects, business stakeholders, and delivery teams.
Innovation & Technical Leadership
- Mentor architects and engineering teams on Java, GenAI, and AI-assisted software development.
- Participate in hackathons and innovation initiatives.
- Develop reusable accelerators, frameworks, and AI assets.
- Drive adoption of emerging AI technologies and engineering practices.
Mandatory Skills Enterprise Java
- 12–15 years of experience in software engineering and architecture.
- Strong hands-on expertise in:
- Java 11/17+
- Spring Boot
- REST APIs
- Microservices
- Distributed Systems
- Event-Driven Architecture
- SQL Databases
GenAI & Agentic AI
- 2–3+ years of hands-on experience with:
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Prompt Engineering
- Embeddings and Vector Databases
- AI Agents / Agentic AI
- Function Calling
AI Frameworks
Hands-on experience with one or more of the following:
- LangChain
- LangGraph
- Semantic Kernel
- LlamaIndex
- CrewAI
- AutoGen
AI Development Tools
Hands-on experience with one or more of the following:
- Windsurf
- Cursor
- GitHub Copilot
- Claude Code
- OpenAI Codex
- Equivalent Agentic IDEs
Cloud & Platforms
- Azure, AWS, or GCP.
- Docker and Kubernetes.
- CI/CD and DevOps.
- AI Security and Responsible AI.
- LLMOps.
- AI Guardrails.
- AI/LLM Observability.
Preferred Candidate Profile
The ideal candidate may come from one of the following backgrounds:
- Senior Java Architect with strong GenAI experience.
- Principal Engineer with a Java and AI background.
- Enterprise Architect with hands-on coding expertise.
- AI Architect with strong enterprise application development experience.
Key Selection Criteria
The successful candidate should be:
- Strong in Enterprise Java Architecture.
- Hands-on with RAG, LLMs, and Agentic AI.
- Experienced in AI-assisted software engineering.
- Customer-facing and consultative.
- Innovation-driven and comfortable participating in hackathons.
- Comfortable working in a hybrid customer environment with 3 days per week onsite.
- Able to collaborate effectively with customer teams, architects, business stakeholders, and delivery teams.