Applied AI Engineer

Requirements:

• 5-8 years of software engineering experience, including at least 2 years focused on AI/ML application development.
• Hands-on experience shipping LLM-powered applications to real users or stakeholders, including RAG pipelines, system-level prompt engineering, and agentic workflows.
• Production-level proficiency in Python and/or TypeScript for rapid prototyping.
• Experience with cloud AI platforms; AWS Bedrock is strongly preferred. SageMaker, Azure AI, or Anthropic Claude are also relevant.
• Working experience with agentic AI frameworks such as LangChain, LangGraph, CrewAI, AWS Strands Agents, Claude Managed Agents, AWS AgentCore, or equivalent.
• Strong API integration skills, including REST, webhooks, MCP, or similar agent-to-service patterns.
• Ability to facilitate business discovery sessions and present proof-of-concept demos to non-technical stakeholders.
• Experience pairing with distributed teams to develop production-grade agentic AI systems.
• Ability to serve as the primary interface between lead AI solutions architects and business stakeholders.
• Strong English communication, executive presence, and disciplined asynchronous documentation.
• Bachelor's degree in computer science, software engineering, AI/ML, or a related field.
• Agile/Scrum experience.
• Ability to build RAG pipelines, API integrations, agentic workflow components, and prompt systems.
• Ability to write transition documentation and contribute to the client's AI and Automation Hub patterns library.

Skills

Bedrock, CrewAI, LLM, LangChain, LangGraph, Large Language Model, Python, RAG, Retrieval Augmented Generation, SageMaker, TypeScript