Senior Generative AI Engineer - Agentic Infrastructure

About Chryselys

Role Summary

Responsibilities

• Design and build agentic infrastructure for memory, context, state, and session management.
• Develop patterns for short-term and long-term agent memory, retrieval, summarization, and context optimization.
• Implement agent-to-agent communication using protocols such as A2A, MCP, and event-driven APIs.
• Build and operate agent workflows using AWS services and AWS AgentCore.
• Integrate agents with tools, enterprise data sources, APIs, and identity systems.
• Establish standards for agent observability, tracing, evaluation, reliability, latency, and cost management.
• Design guardrails for security, privacy, authorization, and responsible agent behavior.
• Collaborate with application engineers to define interfaces between agent runtimes and user-facing products.
• Contribute to reusable frameworks, reference architectures, and engineering best practices for production GenAI systems.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field, with 5+ years of software engineering experience.
• Experience building production-grade GenAI, agentic, or distributed systems.
• Strong programming skills in Python, TypeScript, Java, or a similar language.
• Hands-on experience with agent orchestration frameworks such as LangGraph, LangChain, or comparable technologies.
• Practical experience with AWS, preferably including AWS AgentCore and related services.
• Understanding of agent memory, context windows, retrieval, embeddings, vector databases, and state management.
• Familiarity with A2A, MCP, REST, event-driven architectures, and asynchronous communication patterns.
• Experience with cloud-native development, APIs, containers, CI/CD, and observability.
• Strong understanding of reliability, security, scalability, and operational requirements for enterprise systems.

Preferred Qualifications

• Experience deploying multi-agent systems in production.
• Familiarity with agent evaluation, simulation, and automated testing.
• Experience in healthcare, pharmaceuticals, finance, or another regulated industry.
• Knowledge of IAM, encryption, data governance, and enterprise security practices.
• Ability to communicate complex technical concepts clearly across engineering, product, and business teams.