Senior AI Engineer IRC297440

Role Overview

The AI Systems Engineer on our AI Practice team will design and build production‑grade agentic AI systems that power intelligent automation for our clients. 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 client data ecosystems and beyond to turn complex data signals into reliable, automated action.

What Makes This Role Interesting

• Frontier Technology: Work directly with cutting‑edge agentic frameworks such as LangGraph, LangChain, AgentCore, and MCP.
• Real Impact: Build pipelines that power customer‑facing intelligence, internal automation, and executive decision support for a 40,000‑plus customer base.
• Collaborative Team: Embedded in a small, high‑velocity AI Practice team with direct line to executive leadership and cross‑functional stakeholders in CS, Sales, and Product.

Requirements

We’re looking for a teammate with:

• Hands‑on experience building and shipping agentic AI systems.
• Python Expertise: Primary language, clean, production‑grade code, robust data pipelines, ownership of full lifecycle.
• Agentic Frameworks: Practical experience with LangGraph, LangChain, AgentCore, or comparable multi‑agent orchestration frameworks—including routing, state management, tool use, memory, and evaluation.
• LLM Integration: Demonstrated experience integrating large language models via AWS Bedrock, Anthropic APIs or similar—including prompt engineering, context management, and output validation.
• Data Source Integrations: Hands‑on experience connecting to Snowflake, Apache Iceberg, OpenSearch or similar; familiarity with Cloud Analytics or Talend Cloud a strong plus.
• MCP / Tool‑Use Patterns: Familiarity with Model Context Protocol (MCP) or equivalent patterns for structured access to external data systems.
• API Development: Experience building production REST APIs using FastAPI or comparable Python frameworks.
• Cloud Platforms: Hands‑on AWS experience, Bedrock exposure strongly preferred; familiarity with IAM, Lambda, and API Gateway a plus.

Job Responsibilities

• 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 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.

Benefits

• Work‑Life Balance: Flexible work schedules and support for professional and personal ambitions.
• Professional Development: Dedicated Learning & Development team offering English classes, technical and soft‑skill training, certification support, and opportunities to travel internationally.
• Excellent Benefits: Competitive salaries, family medical insurance, extended paternity leave, annual performance bonuses, and referral bonuses.