My client is a startup looking to transform the way their clients use AI!They are building the next-generation platform for drug launches, starting with a cutting-edge compliance layer. Their vision is to create an AI, Gen AI and Agentic platform that empowers life sciences organizations to navigate their medical, regulatory and legal (MLR) processes seamlessly, accelerate time to market, and drive innovation. This is an opportunity to join a company at the forefront of transforming compliance workflows and setting a new industry standard.
As the Senior/Lead founding AI Engineer, you’ll play a pivotal role in developing the AI, ML and
Gen AI engines and setting our AI technical strategy.
Responsibilities:
● Design, develop, test, deploy, and support the AI and Gen AI agentic engine
including foundation model fine-tuning and/or training, large language model inference,
similarity search, guardrails, model evaluation, experimentation, governance, and
observability, etc.
● Leverage a broad stack of Open Source and SaaS AI technologies such as LLama,
GCP Vertex, AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch,
VLLM, LoRA Adapters, neo4j, etc.
● Leverage state-of-the-art LLM optimization techniques to improve the accuracy and
consistency of our Gen AI engine
● Lead the creation of mulit-agent system using ReAct frameworks such as LangGraph or
CrewAI
● Contribute to the technical vision and the long term roadmap of foundational AI systems
Qualifications:
● Years of experience in software engineering, with a focus on AI, Gen AI and ML
development
● Experience designing, developing, integrating, delivering, and supporting complex AI
systems
● Experience developing AI and ML algorithms or technologies (e.g. LLM training and
fine-tuning, Inference, Similarity Search and VectorDBs, Guardrails, Memory) using
Python, Typescript, C++, or Java
● Passion for staying abreast of the latest AI research and AI systems, and judiciously
apply novel techniques in production
● Hands on experience with prompt structures and fine-tune model outputs to align with
business needs and user expectation
● Excellent communication and presentation skills, with the ability to articulate complex AI
concepts to peers
● Familiarity with cloud infrastructure (AWS, GCP, or Azure).