Associate- BIM

Description

Summary: Seeking highly skilled GenAI Application Leads with expertise in developing and deploying Generative AI applications focused on Data and Analytics in Life Sciences. Highlights: 1. Lead Gen AI Application Development & Engineering in Life Sciences 2. Integrate & fine-tune LLMs like GPT, Claude, and Mistral 3. Drive knowledge-sharing and PoCs to evangelize Generative AI **Position Summary** -------------------- **Highly skilled GenAI Application Leads with 5 to 9 years of total experience** who has worked on development and deployment of Generative AI–based applications **focused on Data and Analytics in Life Sciences domain**. The ideal candidate will have a strong background in Python, RAG, knowledge graphs, Gen AI/LLM frameworks (LangChain, LangGraph), AWS/Azure cloud services with hands\-on experience integrating and fine\-tuning GPT, Anthropic Claude, Mistral, or Snowflake Cortex for real\-world business use cases. Strong client problem\-solving skills across life sciences data and analytics is a plus. **Job Responsibilities** ------------------------ **1\.Gen AI Application Development \& Engineering** * **Build microservices or API layers** that expose AI functionalities securely across teams and systems. * Ensure robust CI/CD pipelines, version control (GitHub, Bitbucket, GitLab), and containerization (Docker, Kubernetes). * Develop user\-centric applications that embed GenAI outputs seamlessly into custom UI or enterprise BI tools like Power BI * Work with data engineering and analytics teams to **connect GenAI apps to existing data ecosystems** (AWS S3, Azure Data Lake, Snowflake, Databricks, etc.) * Use **knowledge graphs and metadata\-driven approaches** to enhance contextual reasoning and data discovery * Deploy AI workloads using **Azure OpenAI,** AWS Sagemaker, Bedrock, or **Snowflake Cortex AI Services**. **2\. AI Model Integration \& Fine\-tuning** * Lead the integration of LLMs (OpenAI GPT, Anthropic Claude, Mistral, Snowflake Cortex, etc.) into enterprise\-grade applications. * Fine\-tune or prompt\-tune foundation models using domain\-specific data (commercial, patient, Omni \-channel, clinical, or market access data). * Support the design of RAG architectures leveraging vector databases (ChromaDB, Pinecone, FAISS, Weaviate etc.). * Develop prompt engineering frameworks and guardrails to ensure factuality, interpretability, and compliance. * Establish evaluation pipelines for model performance, accuracy, latency, and hallucination detection. **3\. Collaboration** * Stay ahead of the curve with emerging LLM architectures, multi\-agent systems, and reasoning frameworks to provide technical guidance to the teams. * Drive **knowledge\-sharing sessions and PoCs** **to evangelize Generative AI adoption** across the organization. **Education** ------------- BE/B.Tech Master of Computer Application**Work Experience** ------------------- **Highly skilled GenAI Application Leads with 5 to 9 years of total experience** who has worked on development and deployment of Generative AI–based applications **focused on Data and Analytics in Life Sciences domain**. The ideal candidate will have a strong background in Python, RAG, knowledge graphs, Gen AI/LLM frameworks (LangChain, LangGraph), AWS/Azure cloud services with hands\-on experience integrating and fine\-tuning GPT, Anthropic Claude, Mistral, or Snowflake Cortex for real\-world business use cases. Strong client problem\-solving skills across life sciences data and analytics is a plus. **Behavioural Competencies** ---------------------------- Ownership Teamwork \& Leadership Cultural Fit Motivation to Learn and Grow**Technical Competencies** -------------------------- Problem Solving Lifescience Knowledge Communication Amazon SageMaker Amazon Redshift Jupyter Notebook Python SQL React**Skills** ----------