About The Company Biorce is a pioneering Healthtech company dedicated to revolutionizing drug development through the power of AI. We are passionate about accelerating medical advancements and improving patient outcomes.

Our team comprises seasoned clinical research professionals, data scientists, and AI experts, working collaboratively to bridge the gap between cutting-edge technology and real-world clinical needs.

With an unwavering commitment to revolutionize healthcare, we envision a world where all patients benefit from accelerated and cost-effective access to treatments. Biorce is poised to redefine the landscape of healthcare, shaping a future where innovation and accessibility converge for the betterment of humanity.

About The Job Mid-Level AI Engineer (Generative AI & Agents)

As an AI Engineer at Biorce, you will focus on building sophisticated AI systems that go beyond simple chat interfaces. You will be responsible for designing agentic workflows , managing complex state in LLM applications, and ensuring that our generative features are reliable, steerable, and scalable.

Key Responsibilities

• Agentic Orchestration: Design and implement complex, multi-step AI workflows using LangGraph or similar frameworks to manage state, loops, and conditional logic.
• Prompt Engineering & Optimization: Develop, test, and version-control advanced prompts (Few-shot, Chain-of-Thought, ReAct). Use Vertex AI's "Help me write" and prompt optimization tools to refine system instructions.
• RAG Pipeline Development: Build and maintain Retrieval-Augmented Generation (RAG) pipelines, including document parsing, embedding optimization, and vector database management.
• LLM Evaluation (LLM-as-a-Judge): Establish automated evaluation frameworks using the Vertex AI Gen AI Evaluation Service to measure hallucination rates, groundedness, and relevancy.

Technical Deep-Dive (Specific Expertise)

• Orchestration: LangGraph (Stateful Actors), LangChain, CrewAI, or Vertex AI Agent Builder.
• GCP Ecosystem: Vertex AI Studio, Cloud Run (for serverless AI apps), BigQuery (for data grounding), and Cloud Storage.
• Data Handling: Advanced RAG techniques (Hybrid search, Parent-Document Retrieval, Query expansion).

Ideal Candidate Profile

• Experience: 2/3+ years in software/ML engineering, with at least 1 year of hands-on experience building and deploying LLM-based applications in production.
• The "Agentic" Mindset: You understand that LLMs are more powerful when treated as reasoning engines within a larger system rather than just text predictors.
• State Management: Deep understanding of how to manage conversational state and memory in complex, non-linear AI graphs (cycles, nodes, and edges).
• Software Rigor: You treat AI engineering like software engineering—applying CI/CD, unit testing for prompts, and structured logging using Cloud Trace and Cloud Logging.