AI Developer

We’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-grade

code, build robust data pipelines, and are comfortable owning the full lifecycle from

prototype to deployment.

• Agentic Frameworks: Practical experience with LangGraph, LangChain, AgentCore, or

comparable multi-agent orchestration frameworks — including agent 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 applications to modern

data platforms including Snowflake, Apache Iceberg, OpenSearch, or similar.

• MCP / Tool-Use Patterns: Familiarity with Model Context Protocol (MCP) or equivalent

patterns for giving agents structured, governed access to external data systems.

• API Development: Experience building production REST APIs using FastAPI or

comparable Python frameworks.

• Cloud Platforms: Hands-on AWS experience, with Bedrock exposure strongly

preferred. Familiarity with IAM, Lambda, and API Gateway a plus.

Beyond technical skills, we’re looking for someone who brings:

• Bias for Action: You ship, instrument, and iterate — you don’t wait for perfect

requirements.

• Strong Communication: Ability to translate complex agentic system behavior to

non-technical stakeholders clearly and concisely.

• Security and Governance Mindset: Awareness of responsible AI practices, data

privacy considerations, and the importance of auditability in agentic systems.

• Collaborative Spirit: Comfortable working across functions and levels, from CSMs to

the C-suite.

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.

• 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.