Senior AI Language Model Engineer

Essential Job Responsibilities

• End-to-end design, research, development, and deployment of language engineering use cases, with continuous client engagement and collaboration.
• Hands-on development in a shared codebase with the team.
• Back-end engineering with AWS, Terraform, etc.
• Working front-end proficiency when needed.
• Design workflows for language model deployment.
• Perform prompt engineering, pre-processing, and post-processing to optimize output suitability.
• Fine-tune and optimize multi-agentic systems to satisfy use case requirements.
• Work with domain experts to assess model quality.

Qualifications

• PhD in Engineering, Computer Science, Data Science, Artificial Intelligence, or a related field.
• Very strong proficiency in Python, with hands-on experience using version control systems.
• Strong foundation in large language models (LLMs) and natural language processing (NLP), with practical experience demonstrated through GitHub repositories, research publications, or a portfolio.
• Familiarity with modern NLP/LLM frameworks and libraries such as LangChain, LangGraph, Hugging Face Transformers, and vector databases.
• Experience with Retrieval-Augmented Generation (RAG), multi-agentic systems, and agentic frameworks (e.g., Strands Agents SDK), with the ability to design, build, and deploy end-to-end AI agents and orchestration pipelines.
• Familiarity with cloud platforms such as AWS (EC2, S3, SageMaker, Bedrock, etc.) through projects.
• Strong communication skills for collaborating with teams and presenting technical results.

Additional Desired Qualifications

• Familiarity with any front-end development (e.g., React) to build user-facing applications.
• Ability to end-to-end develop and deploy full-stack applications — from data ingestion and model development through back-end APIs to front-end interfaces — in addition to the core data science and ML work.
• Experience with database systems (SQL and/or NoSQL) and data pipeline orchestration tools (e.g., Step Functions).
• Experience working in fast-paced, startup-like, or R&D-heavy environments.