AI Automation Engineer, Associate Level

**Job Type: Hybrid (2-3 days a week onsite)** **MUST BE A LOCAL CANDIDATE** \*\* NO Visa Sponsorships or Transfers Available (including OPT) \*\* **Job Overview** Devonshire Recruiting & Consulting Partners is seeking to identify an Associate-level AI Automation Engineer to support the development of intelligent automation capabilities across the organization of a leading tech company. This newly created position is well-suited for an early-career technologist with strong foundational skills and a clear understanding of how modern AI tools can be applied to real-world business workflows.

The role offers exposure to emerging AI frameworks, automation platforms, and agent-based architectures, working closely with consultants and internal stakeholders to design, prototype, and deploy scalable automation solutions that enhance operational efficiency and innovation. **Key Responsibilities** - Design and implement AI-enabled automation workflows and intelligent agents to streamline business processes.

- Integrate large language models and AI services (commercial and open-source) with enterprise systems, including APIs, databases, CRMs, and collaboration tools. - Support rapid prototyping efforts and assist in transitioning proofs of concept into production-ready solutions. - Test, debug, and optimize automation scripts and AI agents for reliability and performance. - Monitor developments in AI tooling, frameworks, and platforms to identify opportunities for innovation.

- Create and maintain technical documentation to support knowledge sharing and long-term maintainability. **Required Qualifications** - Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical discipline. - 1–2 years of relevant professional experience in automation, software development, or applied AI. - Proficient in Python, including experience with scripting, APIs, or workflow automation.

- Working knowledge of AI concepts such as large language models, prompt design, and natural language processing. - Familiarity with agent-based or orchestration frameworks (e.g., LangChain, LangGraph, Pydantic AI, CrewAI, or similar). - Exposure to retrieval-augmented generation (RAG) patterns and AI tool integration concepts. - Experience with workflow or ETL tools, either open-source (e.g., Airflow, Prefect, DBT) or platform-based (e.g., Databricks, GCP Workflows, Azure Data Factory).

- Basic understanding of cloud environments (AWS, Azure, or GCP) and version control systems such as Git. - Strong analytical mindset, curiosity, and ability to learn new technologies quickly. - Solid communication skills with the ability to collaborate effectively across technical and non-technical teams.