Generative AI Engineer

About Us:

Chryselys is a 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.

Who we are:

• People - Our team of industry veterans, advisors and senior strategists have diverse backgrounds and have worked at top tier companies.
• Quality - Our goal is to deliver the value of a big five consulting company without the big five cost.
• Technology - Our solutions are Business centric built on cloud native technologies.

Senior GenAI / Agentic Systems Engineer

We are looking for a Senior GenAI / Agentic Systems Engineer to design, build and operate production-grade AI systems that combine LLMs, agents, retrieval, memory and distributed cloud services.

The ideal candidate is a strong software engineer who has moved beyond GenAI experimentation and has hands-on experience taking agentic and AI-powered systems from prototype to reliable production deployments. You will work across agent orchestration, context and state management, RAG, tool integration, distributed services and cloud infrastructure, with a strong focus on reliability, security, scalability and observability.

Key Responsibilities

• Design and develop production-grade GenAI and agentic systems using modern LLM, agent and distributed-systems architectures.
• Build agent workflows incorporating memory, context, state and session management, ensuring agents can maintain the right information across interactions and workflows.
• Design and implement RAG pipelines, including embeddings, chunking, retrieval, reranking and integration with vector databases.
• Develop sophisticated agent orchestration using LangGraph, LangChain and AWS AgentCore.
• Build and integrate tools, APIs and external services using REST, MCP, A2A and event-driven interfaces.
• Design architectures for single-agent and multi-agent systems, including agent-to-agent coordination, delegation and workflow management.
• Develop scalable backend services using Python, TypeScript and/or Java.
• Build cloud-native services on AWS, leveraging managed services and serverless/containerized architectures where appropriate.
• Develop containerized applications and production deployment pipelines using Docker, CI/CD and infrastructure automation.
• Establish robust observability across AI and distributed systems, including logging, metrics, tracing, model/agent behavior and operational monitoring.
• Engineer for reliability, scalability, performance and fault tolerance, including graceful degradation and failure recovery for AI workflows.
• Implement enterprise-grade security and governance, including IAM, encryption, secrets management, access controls and data governance.
• Design systems that appropriately handle sensitive and regulated data, with strong controls around data access, retention, auditability and lineage.
• Collaborate with product, frontend, AI/ML, platform and DevOps teams to translate business requirements into scalable technical solutions.
• Drive technical decisions, architecture evolution, engineering standards and best practices across the GenAI platform.
• Evaluate emerging agent frameworks, protocols, models and infrastructure patterns, and determine where they provide meaningful production value.

Required Experience & Skills

• 5+ years of software engineering experience, with hands-on experience building production GenAI, agentic or distributed systems.
• Strong programming experience in one or more of Python, TypeScript or Java.
• Deep understanding of LLM and agent architectures, including prompting, tool calling, orchestration and structured outputs.
• Strong hands-on experience with agent memory, context management, state management and session management.
• Production experience with RAG, embeddings and vector databases.
• Hands-on experience with LangGraph and/or LangChain.
• Experience with AWS and AWS AgentCore.
• Strong understanding of modern AI interoperability and service protocols, including MCP, A2A and REST APIs.
• Experience designing event-driven and distributed systems.
• Experience with containers, CI/CD and cloud-native deployment practices.
• Strong understanding of observability, including logs, metrics, tracing, alerting and production diagnostics.
• Strong engineering fundamentals around reliability, security, scalability, performance and fault tolerance.
• Practical experience with AWS IAM, encryption, secrets management and data governance.
• Experience designing systems for production workloads rather than purely experimental or proof-of-concept environments.

How to Apply:

Ready to make an impact? Apply now by clicking [here] or visit our careers page at https://chryselys.com/chryselys-career/

Please include your resume and a cover letter detailing why you're the perfect fit for this role.

Equal Employment Opportunity:

Chryselys is proud to be an Equal Employment Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Connect with Us:

Follow us for updates and more opportunities: https://www.linkedin.com/company/chryselys/mycompany/

Discover more about our team and culture: www.chryselys.com