Work Shift: Monday through Friday 09:00 am to 06:00 pm

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

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

This is a high-visibility opportunity where your software engineering expertise will directly impact our Customer’s engineering user experiences.

Originally posted on Himalayas

Software Engineer AI - Artificial Intelligence

Job Description