Requirements

2+ years of software engineering experience
Experience with applied AI, or automation engineering experience
Experience with Python and agentic frameworks (e.g., LangChain, LlamaIndex, AutoGen)
Experience designing and deploying agents using tools (e.g., Crew AI, Agentuity, n8n)
Proficiency with prompt engineering, memory strategies, and tool/function calling
Ability to collaborate across departments to deliver AI solutions and promote adoption
Ability to support business stakeholders in adapting workflows to agentic systems
Experience managing delivery timelines and defining project success metrics
Strong communication skills in both spoken and written English

What you will work on

Design, build, and manage LLM-based agents that automate internal operations across departments (e.g., Engineering, Product, Sales, HR, Field Operations)
Identify high-impact use cases and deliver tailored agentic solutions from scoping to scaling
Own the full lifecycle of AI-powered automations, ensuring seamless integration and long-term reliability
Collaborate with product managers, engineers, and stakeholders to embed agents into real-world workflows
Promote adoption by partnering with department leads to evolve processes and drive behavior change
Design agentic systems using frameworks (e.g. Crew AI, Agentuity) to support complex workflows
Integrate APIs and tools using automation platforms (e.g. n8n, Zapier, Make.com)
Implement advanced techniques like prompt chaining, memory strategies, RAG, and tool-calling
Monitor, maintain, and optimize deployed agents for performance, uptime, and value delivery
Establish governance, testing, and issue resolution processes for production agents
Lead agentic project plans, delivery timelines, and milestone tracking
Document agent behavior, system logic, testing protocols, and maintenance procedures
Report on solution performance, ROI, and progress to leadership and contribute to automation strategy