Job Level
Mid-LevelSenior
Tech Stack
AWSAzureCloudGoogle Cloud Platform
About the role
- Rapidly prototype, test, and deploy AI-powered tools such as copilots, automations, knowledge assistants, and agents
- Implement RAG pipelines, prompt engineering, and orchestration frameworks (LangChain, LlamaIndex, etc.)
- Partner with business teams to understand workflows and identify opportunities for AI acceleration
- Work closely with data, engineering, and security teams to ensure reliability, scalability, and compliance of deployed solutions
- Maintain and contribute to a backlog of AI initiatives, prioritizing those with clear business impact
- Monitor performance and adoption, track KPIs, and iterate on solutions to maximize effectiveness
- Contribute to internal documentation, demos, and training to help colleagues become fluent AI users
- Provide technical support during workshops, office hours, and stakeholder pilots
- Evaluate emerging AI platforms, frameworks, and APIs with a pragmatic lens for business value
- Share insights with the team and contribute to scaling best practices into playbooks and repeatable patterns
Requirements
- Strong hands-on experience as a technical IC (e.g., software engineering, ML, data engineering, or automation)
- Proficiency with modern AI tooling (OpenAI, Claude, LangChain, Hugging Face, vector DBs, agents, RAG pipelines)
- Demonstrated ability to scope, build, and deliver working solutions from idea to impact
- Solid understanding of APIs, data pipelines, and software deployment practices
- Excellent problem-solving and communication skills. You can explain technical concepts clearly and engage with non-technical stakeholders
- Experience with cloud platforms (AWS, GCP, Azure) and containerized deployments (preferred). Previous work on copilots, chatbots, or workflow automation tools (preferred)
- Strong product sense, you can see through the hype to spot practical, high-leverage use cases (preferred)