AI Architect - Enterprise Java, GenAI & AI-Powered Engineering - 26-13312
Compu-Vision - IT
Job Description
Job Description
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
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.
- 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.
- 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.
- 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.
- 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.
- 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
- 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
Hands-on experience with one or more of the following:
- LangChain
- LangGraph
- Semantic Kernel
- LlamaIndex
- CrewAI
- AutoGen
Hands-on experience with one or more of the following:
- Windsurf
- Cursor
- GitHub Copilot
- Claude Code
- OpenAI Codex
- Equivalent Agentic IDEs
- Azure, AWS, or GCP.
- Docker and Kubernetes.
- CI/CD and DevOps.
- AI Security and Responsible AI.
- LLMOps.
- AI Guardrails.
- AI/LLM Observability.
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.
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.
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