Generative AI Engineer, LLM & RAG Systems
Overview
You will own the design and delivery of GenAI prototypes and workflows at enterprise scale across financial services. You will join the Business Support team, reporting to the AI Engineering lead. You will research emerging AI technologies, build LLM-based solutions, and benchmark models to drive adoption. 3+ years of hands-on Python and GenAI experience is required. This role offers direct collaboration with engineering teams to ship production-ready AI innovations.
What You'll Do8
- 1Research emerging GenAI technologies and publish findings for the team.
- 2Develop rapid prototypes of LLM-based applications and present demos to stakeholders.
- 3Build GenAI workflows using LangChain, RAG, and vector databases.
- 4Benchmark LLMs (e.g., GPT-4, Llama) on accuracy, latency, and cost.
- 5Collaborate with data engineers to integrate GenAI solutions into existing pipelines.
- 6Drive the transition of prototypes to production, ensuring scalability and reliability.
- 7Debug and fine-tune LLM outputs to meet business requirements.
- 8Document architecture and code for maintainability and knowledge sharing.
Requirements7
- 13+ years of experience in AI engineering with a focus on GenAI.
- 21+ years building LLM-based applications with RAG or LangChain.
- 3Proficiency in Python and frameworks like PyTorch or TensorFlow.
- 4Experience with cloud platforms such as AWS, Azure, or GCP for model deployment.
- 5Hands-on knowledge of vector databases like Pinecone or Weaviate.
- 6Strong understanding of transformer architectures and LLM fine-tuning techniques.
- 7Ability to work onsite in Boston, MA, Hartford, CT, Princeton, NJ, Newark, NJ, or New York City, NY.
Salary Insight
Salary not disclosed in listing
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