Senior IA Engineer Python AWS

Job DescriptionWe’re looking for a teammate with:The ideal candidate will have hands-on experience building and shipping agentic AI systems,with deep proficiency in Python and the modern AI engineering stack:• Python Expertise: Python is your primary language. You write clean, production-gradecode, build robust data pipelines, and are comfortable owning the full lifecycle fromprototype to deployment.• Agentic Frameworks: Practical experience with LangGraph, LangChain, AgentCore, orcomparable multi-agent orchestration frameworks — including agent routing, statemanagement, tool use, memory, and evaluation.• LLM Integration: Demonstrated experience integrating large language models via AWSBedrock, Anthropic APIs, or similar — including prompt engineering, contextmanagement, and output validation.• Data Source Integrations: Hands-on experience connecting applications to moderndata platforms including Snowflake, Apache Iceberg, OpenSearch, or similar.• MCP / Tool-Use Patterns: Familiarity with Model Context Protocol (MCP) or equivalentpatterns for giving agents structured, governed access to external data systems.• API Development: Experience building production REST APIs using FastAPI orcomparable Python frameworks.• Cloud Platforms: Hands-on AWS experience, with Bedrock exposure stronglypreferred. Familiarity with IAM, Lambda, and API Gateway a plus.

Job ResponsibilitiesHere’s how you’ll be making an impact:• Build Multi-Agent Pipelines: Design and implement orchestrated multi-agent systemsusing LangGraph and AgentCore, including routing logic, evaluation loops, retrymechanisms, and agent specialization patterns.• Develop with LangChain: Leverage LangChain to build sophisticated prompt pipelines,tool-augmented agents, memory constructs, and retrieval-augmented generationworkflows.• Integrate Across the Data Ecosystem: Build reliable, performant Python integrationsconnecting agents to client Cloud Analytics, Snowflake, ApacheIceberg, OpenSearch, and other data sources via MCP and direct API patterns.• Deploy on AWS Bedrock: Leverage AWS Bedrock to host, invoke, and manageLLM-powered agents at scale, ensuring reliability, cost efficiency, and securitycompliance.• Build FastAPI Services: Develop lightweight, production-ready API services thatexpose 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, andAnalytics stakeholders to translate business requirements into agentic architectures
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