Design and build scalable infrastructure for production-grade generative AI agents, including memory, context, state, session management, orchestration, agent-to-agent communication, tool integration, observability, reliability, security, and cost optimization. Collaborate with application, platform, and product teams to establish reusable frameworks and architectures for secure enterprise agentic systems.
About Chryselys
Chryselys is a Great Place to Work Certified Pharma Analytics & Business consulting company that delivers data-driven insights leveraging AI-powered, cloud-native platforms to achieve high-impact transformations. We specialize in digital technologies and advanced data science techniques that provide strategic and operational insights.
Role SummaryWe are seeking a Generative AI Engineer to design and build the infrastructure that enables reliable, scalable, and intelligent agentic applications. This role focuses on the systems behind AI agents — including memory, context management, agent-to-agent communication, orchestration, and runtime operations. You will partner with application, platform, and product teams to develop the foundations that allow agents to collaborate, retain relevant information, use tools effectively, and operate securely in enterprise environments.
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.
- 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.
- 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.
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