Software Engineer V

Key Responsibilities

• Design, build, deploy, and support enterprise-grade AI solutions in production environments.
• Develop and optimize agentic workflows, orchestration pipelines, and tool integrations.
• Create and enhance Retrieval-Augmented Generation (RAG) and agent-based architectures.
• Implement evaluation frameworks to improve AI groundedness, quality, and system reliability.
• Implement observability, tracing, and monitoring capabilities for AI systems to ensure performance and stability.
• Develop automated testing and regression validation processes for AI solutions.
• Partner with stakeholders to translate business needs into scalable AI architectures and components.
• Contribute to establishing engineering best practices, code reviews, and reusable frameworks.

Required Skills & Experience

• 5 or more years of professional software engineering experience.
• Proven success delivering enterprise-grade production software.
• Strong Python programming skills.
• Hands-on experience building, deploying, and operating production AI systems—especially with RAG solutions.
• Experience with Databricks and LangGraph or similar agent orchestration frameworks.
• Knowledge of AI evaluation frameworks, observability, and tracing solutions.
• Familiarity with agent architecture patterns, prompt engineering, and large language model (LLM) evaluation techniques.
• Experience working within AWS production environments.
• Proficiency designing and consuming REST APIs.
• Strong understanding of Git, CI/CD pipelines, and modern development practices.
• Knowledge of secure coding principles and responsible AI practices.
• Bachelor’s degree in Computer Science, Engineering, or related discipline.

Desired Skills & Experience

• Experience with AgentBricks and LangChain frameworks.
• Familiarity with AI tooling like MLflow, Grafana, or DeepEval.
• Certification in AWS, Databricks, or related AI domains.
• Exposure to multi-agent system deployment and Terraform infrastructure management.