Description
Summary:
Seeking highly skilled GenAI Application Leads with expertise in developing and deploying Generative AI applications focused on Data and Analytics in the Life Sciences domain.
Highlights:
1. Lead Gen AI application development and engineering in Life Sciences
2. Integrate and fine-tune LLMs like GPT, Claude, and Mistral
3. Drive knowledge-sharing and PoCs to evangelize Generative AI adoption
**Position Summary**
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**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**
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**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**
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BE/B.Tech
Master of Computer Application**Work Experience**
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**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**
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Ownership
Teamwork \& Leadership
Cultural Fit
Motivation to Learn and Grow**Technical Competencies**
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Problem Solving
Lifescience Knowledge
Communication
Amazon SageMaker
Amazon Redshift
Jupyter Notebook
Python
SQL
React**Skills**
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