You should have:

- 5+ years of professional software engineering experience.

- Strong hands-on experience with Python.

- Experience with TypeScript, JavaScript, or Java is highly desirable.

- Approximately 2+ years of experience working with Generative AI, RAG, or AI-powered applications.

- Experience designing and deploying production-grade RAG solutions.

- Experience building agentic AI systems or autonomous workflows used by real users.

- The ability to take technical ownership and confidently explain and defend your architectural decisions.

- Strong software engineering fundamentals, including APIs, distributed systems, testing, reliability, and production deployment.

Agent Frameworks:

- Experience with at least one of:

1. LangGraph

2. LangChain

3. AutoGen

4. CrewAI

5. Semantic Kernel

6. Other comparable AI orchestration frameworks

AI Engineering:

- Hands-on experience with:

1. RAG architecture and implementation

2. Agentic workflows

3. Prompt and context engineering

4. Tool and API integration

5. Workflow orchestration

6. Agent state and memory

7. Failure handling and recovery

8. AI evaluation and testing

9. Observability and monitoring

10. Latency and cost optimization

AI-Assisted Software Development:

- You actively use AI to improve the way you build software.

- Experience with tools such as:

1. Claude Code

2. GitHub Copilot

3. Cursor

4. Windsurf

5. Other AI-assisted development tools

- This is an opportunity to work on some of the most exciting challenges in modern software engineering.

Intersection of Fields:

- You will be at the intersection of: Generative AI, Agentic AI, Software Engineering, and Enterprise Transformation.

Opportunities:

- Build next-generation AI systems used in a global enterprise.

- Work hands-on with rapidly evolving AI technologies.

- Influence the organization's AI engineering strategy.

- Experiment with emerging platforms and tools.

- Create reusable technology that enables hundreds of engineers.

- Work on challenging problems involving scale, reliability, security, governance, and cost.

- Help define how AI changes the future of software development.