Position: Software Engineer AI
Location: Remote
Work Shift: Monday through Friday 09:00 am to 06:00 pm
Benefits:
·Christmas Bonus
·Vacation Bonus
·Flexible Compensation
·Food Vouchers
·Saving Fund
·Work Tools
·Employee Profit Sharing
·Performance Bonus
·Birthday Leave
·Major Medical Insurance
·Life Insurance
·Retirement Plan
·Company Cafeteria Service
·Reliable Transportation
Requirements:
- Bachelor’s degree in Computer Science, Computer Engineering, Machine Learning, or related technical field
- 5+ years of professional software engineering experience with strong proficiency in Python and experience with Java
- 2+ years of hands-on production GenAI experience, including:
- Building and deploying AI Agentic systems or autonomous agents in production environments
- Architecting context engineering solutions including dynamic context assembly, memory systems, and agentic retrieval patterns
- Designing multi-agent orchestration and multi-hop reasoning pipelines
- Implementing agent planning strategies, tool orchestration, and human-in-the-loop patterns
- Prompt engineering, function calling, and tool-use implementations
- Proven track record of shipping production-grade AI/ML systems that delivered measurable business value
- Strong experience with agentic frameworks, particularly ADK (Agentic Design Kit) and LangGraph, or similar modern agent orchestration tools
- Strong understanding of software design patterns, SOLID principles, and clean architecture applied to AI systems
- Experience with CI/CD pipelines, containerization (Docker), and cloud infrastructure
Key Responsabilities:
- Design and Deploy Production AI Agentic Systems: Architect, build, and deploy autonomous AI agents using state-of-the-art frameworks like ADK (Agentic Design Kit) and LangGraph that leverage LLMs to automate code reviews, quality analysis, and development workflow optimization at scale
- Architect Advanced Context Engineering Solutions: Design sophisticated context engineering strategies including dynamic context assembly, agentic retrieval patterns, memory systems (episodic and working memory), and multi-hop reasoning pipelines for complex code analysis tasks
- Develop AI-Powered Automation Tools: Build intelligent backend services in Python and Java that leverage GenAI to detect anti-patterns, suggest improvements, and standardize development workflows
- Establish AI-Enhanced Engineering Excellence: Define and implement coding standards and best practices specifically for GenAI systems, including LLM evaluation metrics, guardrails, and responsible AI principles
- Lead AI-Powered Code Reviews: Conduct comprehensive code reviews using state-of-the-art GenAI tools and agents, providing architectural guidance on performance, security, and AI system design
Contact Details:[email protected]
This is a high-visibility opportunity where your software engineering expertise will directly impact our Customer’s engineering user experiences.
Originally posted on