The AI Systems Engineer Role As an AI Systems Engineer on the AI Practice team, you will design and build production-grade agentic AI systems that power the next generation of intelligent automation at our client project. Reporting to the Global Head of AI Strategy, Policy, and Governance, you will work at the frontier of multi‑agent orchestration—connecting large language models to the client’s data ecosystem and beyond, turning complex data signals into reliable, automated action. Why this role is interesting Frontier Technology: You’ll work directly with cutting‑edge agentic frameworks—LangGraph, LangChain, AgentCore, MCP—building systems that most engineers are only reading about. Real Impact: The pipelines you build will directly power customer‑facing intelligence, internal automation, and executive decision support across a 40,000+ customer base. Collaborative Team: You’ll be embedded in a small, high‑velocity AI Practice team with a direct line to executive leadership and cross‑functional stakeholders across CS, Sales, and Product. Requirements We’re looking for a teammate with: Hands‑on experience building and shipping agentic AI systems, with deep proficiency in Python and the modern AI engineering stack. Python expertise: Writing clean, production‑grade code, building robust data pipelines, and owning the full lifecycle from prototype to deployment. Practical experience with LangGraph, LangChain, AgentCore, or comparable multi‑agent orchestration frameworks—including agent routing, state management, tool use, memory, and evaluation. Demonstrated experience integrating large language models via AWS Bedrock, Anthropic APIs, or similar—including prompt engineering, context management, and output validation. Hands‑on experience connecting applications to modern data platforms such as Snowflake, Apache Iceberg, OpenSearch, or similar, and familiarity with Cloud Analytics or Talend Cloud for a strong plus. Familiarity with Model Context Protocol (MCP) or equivalent patterns for giving agents structured, governed access to external data systems. Experience building production REST APIs using FastAPI or comparable Python frameworks. Hands‑on AWS experience, with Bedrock exposure strongly preferred, and familiarity with IAM, Lambda, and API Gateway as a plus. Job responsibilities Here’s how you’ll be making an impact: Build multi‑agent pipelines: Design and implement orchestrated multi‑agent systems using LangGraph and AgentCore, including routing logic, evaluation loops, retry mechanisms, and agent specialization patterns. Develop with LangChain: Leverage LangChain to build sophisticated prompt pipelines, tool‑augmented agents, memory constructs, and retrieval‑augmented generation workflows. Integrate across the data ecosystem: Build reliable, performant Python integrations connecting agents to Qlik Cloud Analytics, Qlik Talend Cloud, Snowflake, Apache Iceberg, OpenSearch, and other data sources via MCP and direct API patterns. Connect via MCP: Develop and maintain Python‑based integrations with Qlik’s MCP server to give agents real‑time, structured access to Qlik platform data and telemetry. Deploy on AWS Bedrock: Leverage AWS Bedrock to host, invoke, and manage LLM‑powered agents at scale, ensuring reliability, cost efficiency, and security compliance. Build FastAPI services: Develop lightweight, production‑ready API services that expose agentic capabilities to downstream consumers and orchestration platforms. Iterate rapidly: Operate in a fast‑moving incubator environment—prototype quickly, instrument your work, and evolve solutions based on real usage signals. Collaborate cross‑functionally: Partner closely with Customer Success, Sales, and Analytics stakeholders to translate business requirements into agentic architectures. What we offer Exciting projects: Work across industries and sectors on market‑defining products using the latest technologies. Collaborative environment: Expand your skills by collaborating with a diverse team of highly talented people in an open, laidback environment—including opportunities abroad in our global centers or client facilities. Work‑life balance: GlobalLogic prioritizes work‑life balance with flexible work schedules. Professional development: Dedicated Learning & Development teams organize English classes, professional certifications, and technical and soft‑skill training, with opportunities to travel internationally. Excellent benefits: Competitive salaries, family medical insurance, extended paternity leave, annual performance bonuses, and referral bonuses. Legal & EEO Statement Gender * The gender information on this form helps us understand the makeup of our applicant pool in this key area, and to continuously improve our efforts to make our workforce more inclusive. #J-18808-Ljbffr