AI Engineer
Description For AI Engineer
Beamery is seeking an AI Engineer to join their Edge team, focusing on transforming how organizations manage talent and plan their workforce. The role combines cutting-edge AI technology with practical business applications in the HR tech space. As an AI Engineer, you'll work on building intelligent products powered by LLMs and agentic workflows, processing complex talent data into actionable insights and automation.
The position sits within Beamery Edge, which creates a data-and-computation environment for large-scale experimentation with unique data assets. The team combines data, analytics, and science to build a multimodal knowledge base, enabling solutions such as information extraction, entity resolution, graph-based embeddings, and search. You'll be part of a globally distributed group tackling novel R&D problems that directly impact customers.
The technology stack includes Python, Agentic tools (Autogen, Semantic Kernel, LangChain), SQL, MongoDB, Third-party LLM APIs, LiteLLM, MLflow, Google Cloud Platform, Docker, PyTorch, Hugging Face Transformers, SPARQL, and Kubernetes. The role offers an opportunity to work with emerging technologies while solving real-world problems in talent management.
Beamery's mission focuses on creating equal access to work, skills, and careers, serving Fortune 2000 organizations globally. The company is at an exciting phase, deepening integrations with major platforms like SAP, Workday, Microsoft, and LinkedIn, while advancing their use of proprietary LLMs and knowledge graph technology. They maintain a strong focus on company culture built on trust, empathy, and honesty, with a commitment to diversity and inclusion.
Responsibilities For AI Engineer
- Build and deploy ML systems that process and reason over complex, semi-structured text
- Transform customer data into actionable insights through machine learning
- Explore emerging research in LLMs, multi-agent workflows, RAG, and recommendation systems
- Prototype quickly and experiment with new models and techniques
- Work with software teams to integrate ML capabilities into production systems
- Design robust evaluation pipelines and datasets to test model performance
Requirements For AI Engineer
- Proven experience delivering ML projects across the full development lifecycle
- Strong foundation in NLP and GenAI, including experience with Transformers, LLMs, RAG pipelines
- Familiarity with search and recommendation systems
- Solid grasp of software engineering best practices
- Ability to collaborate effectively across functions
- Experience with CI/CD workflows, testing, and scalable ETL pipelines
