Senior Associate Solution Architect (Agentic Automation, GenAI & ML)
Amgen
Senior Associate Solution Architect (Agentic Automation, GenAI & ML)
Job Description
At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.
What you will do
- Build and maintain full-stack AI applications, ensuring performance, scalability, and cost-efficiency.
- Design and implement agentic AI systems that autonomously perform complex tasks, leveraging LLMs, multi-agent orchestration, and tool integration.
- Collaborate cross-functionally with data scientists, engineers, and product teams to drive innovation and platform reuse.
- Stay current with the latest trends in generative AI, multi-modal models, and agent frameworks (e.g., LangChain, Langgraph, AutoGen, CrewAI).
- Design, develop, and deploy automation workflows using platforms such as UiPath and Power Automate.
What we expect of you
- Master's degree / Bachelor's degree and 5 to 9 years of Life Science/Biotechnology/Pharmacology/Information Systems experience.
- 3+ years of experience in AI/ML system architecture and deployment.
- Experience with agentic AI frameworks and multi-agent orchestration.
- Experience in Pharma and Biopharma industry preferred but will consider any healthcare industry experience.
Must-Have Skills
- Proficiency in Python, ML frameworks (e.g., TensorFlow, PyTorch), and cloud platforms (AWS, Azure, or GCP).
- Hands-on experience with MLOps tools and AI model lifecycle management.
- Strong understanding of LLM-based architecture, prompt engineering, and fine-tuning techniques.
- Proficient in all aspects like design, develop and deploy automation workflows using platforms such as UiPath and Power Automate.
- Business Processing Modeling: Proficiency in using business modeling techniques like UML or BPMN.
- Familiarity with vector databases and retrieval-augmented generation (RAG).
- Knowledge of Architecting and deploying end-to-end machine learning pipelines using modern MLOps stacks such as Kubeflow, Amazon SageMaker, and OpenAI SDK.
- Optimize AI workloads for cloud-native environments, ensuring robust CI/CD, monitoring, and governance.
- Experience with observability tools and model monitoring platforms.
- Awareness and use of responsible AI practices, including model explainability, fairness, and observability.
- Knowledge of modern SAP platforms and modules, preferably in S4 and Build Process Automation (BPA) suite.
- Strong solution design and problem-solving skills.
- Strong understanding of technology, function, or platform.
- Ability to analyze client requirements and translate them into solutions.
- API Integration Technologies: Familiarity with integration platforms, protocols, and standards (e.g., ESB, REST, SOAP).
- Excellent critical-thinking and problem-solving skills.
- Strong communication and collaboration skills.
- Demonstrated awareness of how to function in a team setting.
- Demonstrated awareness of presentation skills.
Locations
- Hyderabad, India
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
30,000 - 50,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Proficiency in Python, ML frameworks (e.g., TensorFlow, PyTorch), and cloud platforms (AWS, Azure, or GCP).intermediate
- Hands-on experience with MLOps tools and AI model lifecycle management.intermediate
- Strong understanding of LLM-based architecture, prompt engineering, and fine-tuning techniques.intermediate
- Proficient in all aspects like design, develop and deploy automation workflows using platforms such as UiPath and Power Automate.intermediate
- Business Processing Modeling: Proficiency in using business modeling techniques like UML or BPMN.intermediate
- Familiarity with vector databases and retrieval-augmented generation (RAG).intermediate
- Knowledge of Architecting and deploying end-to-end machine learning pipelines using modern MLOps stacks such as Kubeflow, Amazon SageMaker, and OpenAI SDK.intermediate
- Optimize AI workloads for cloud-native environments, ensuring robust CI/CD, monitoring, and governance.intermediate
- Experience with observability tools and model monitoring platforms.intermediate
- Awareness and use of responsible AI practices, including model explainability, fairness, and observability.intermediate
- Knowledge of modern SAP platforms and modules, preferably in S4 and Build Process Automation (BPA) suite.intermediate
- Strong solution design and problem-solving skills.intermediate
- Strong understanding of technology, function, or platform.intermediate
- Ability to analyze client requirements and translate them into solutions.intermediate
- API Integration Technologies: Familiarity with integration platforms, protocols, and standards (e.g., ESB, REST, SOAP).intermediate
- Excellent critical-thinking and problem-solving skills.intermediate
- Strong communication and collaboration skills.intermediate
- Demonstrated awareness of how to function in a team setting.intermediate
- Demonstrated awareness of presentation skills.intermediate
Required Qualifications
- Master's degree / Bachelor's degree and 5 to 9 years of Life Science/Biotechnology/Pharmacology/Information Systems experience. (experience)
- 3+ years of experience in AI/ML system architecture and deployment. (experience)
- Experience with agentic AI frameworks and multi-agent orchestration. (experience)
- Experience in Pharma and Biopharma industry preferred but will consider any healthcare industry experience. (experience)
Responsibilities
- Build and maintain full-stack AI applications, ensuring performance, scalability, and cost-efficiency.
- Design and implement agentic AI systems that autonomously perform complex tasks, leveraging LLMs, multi-agent orchestration, and tool integration.
- Collaborate cross-functionally with data scientists, engineers, and product teams to drive innovation and platform reuse.
- Stay current with the latest trends in generative AI, multi-modal models, and agent frameworks (e.g., LangChain, Langgraph, AutoGen, CrewAI).
- Design, develop, and deploy automation workflows using platforms such as UiPath and Power Automate.
Tags & Categories
Senior Associate Solution Architect (Agentic Automation, GenAI & ML)
Amgen
Senior Associate Solution Architect (Agentic Automation, GenAI & ML)
Job Description
At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.
What you will do
- Build and maintain full-stack AI applications, ensuring performance, scalability, and cost-efficiency.
- Design and implement agentic AI systems that autonomously perform complex tasks, leveraging LLMs, multi-agent orchestration, and tool integration.
- Collaborate cross-functionally with data scientists, engineers, and product teams to drive innovation and platform reuse.
- Stay current with the latest trends in generative AI, multi-modal models, and agent frameworks (e.g., LangChain, Langgraph, AutoGen, CrewAI).
- Design, develop, and deploy automation workflows using platforms such as UiPath and Power Automate.
What we expect of you
- Master's degree / Bachelor's degree and 5 to 9 years of Life Science/Biotechnology/Pharmacology/Information Systems experience.
- 3+ years of experience in AI/ML system architecture and deployment.
- Experience with agentic AI frameworks and multi-agent orchestration.
- Experience in Pharma and Biopharma industry preferred but will consider any healthcare industry experience.
Must-Have Skills
- Proficiency in Python, ML frameworks (e.g., TensorFlow, PyTorch), and cloud platforms (AWS, Azure, or GCP).
- Hands-on experience with MLOps tools and AI model lifecycle management.
- Strong understanding of LLM-based architecture, prompt engineering, and fine-tuning techniques.
- Proficient in all aspects like design, develop and deploy automation workflows using platforms such as UiPath and Power Automate.
- Business Processing Modeling: Proficiency in using business modeling techniques like UML or BPMN.
- Familiarity with vector databases and retrieval-augmented generation (RAG).
- Knowledge of Architecting and deploying end-to-end machine learning pipelines using modern MLOps stacks such as Kubeflow, Amazon SageMaker, and OpenAI SDK.
- Optimize AI workloads for cloud-native environments, ensuring robust CI/CD, monitoring, and governance.
- Experience with observability tools and model monitoring platforms.
- Awareness and use of responsible AI practices, including model explainability, fairness, and observability.
- Knowledge of modern SAP platforms and modules, preferably in S4 and Build Process Automation (BPA) suite.
- Strong solution design and problem-solving skills.
- Strong understanding of technology, function, or platform.
- Ability to analyze client requirements and translate them into solutions.
- API Integration Technologies: Familiarity with integration platforms, protocols, and standards (e.g., ESB, REST, SOAP).
- Excellent critical-thinking and problem-solving skills.
- Strong communication and collaboration skills.
- Demonstrated awareness of how to function in a team setting.
- Demonstrated awareness of presentation skills.
Locations
- Hyderabad, India
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
30,000 - 50,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Proficiency in Python, ML frameworks (e.g., TensorFlow, PyTorch), and cloud platforms (AWS, Azure, or GCP).intermediate
- Hands-on experience with MLOps tools and AI model lifecycle management.intermediate
- Strong understanding of LLM-based architecture, prompt engineering, and fine-tuning techniques.intermediate
- Proficient in all aspects like design, develop and deploy automation workflows using platforms such as UiPath and Power Automate.intermediate
- Business Processing Modeling: Proficiency in using business modeling techniques like UML or BPMN.intermediate
- Familiarity with vector databases and retrieval-augmented generation (RAG).intermediate
- Knowledge of Architecting and deploying end-to-end machine learning pipelines using modern MLOps stacks such as Kubeflow, Amazon SageMaker, and OpenAI SDK.intermediate
- Optimize AI workloads for cloud-native environments, ensuring robust CI/CD, monitoring, and governance.intermediate
- Experience with observability tools and model monitoring platforms.intermediate
- Awareness and use of responsible AI practices, including model explainability, fairness, and observability.intermediate
- Knowledge of modern SAP platforms and modules, preferably in S4 and Build Process Automation (BPA) suite.intermediate
- Strong solution design and problem-solving skills.intermediate
- Strong understanding of technology, function, or platform.intermediate
- Ability to analyze client requirements and translate them into solutions.intermediate
- API Integration Technologies: Familiarity with integration platforms, protocols, and standards (e.g., ESB, REST, SOAP).intermediate
- Excellent critical-thinking and problem-solving skills.intermediate
- Strong communication and collaboration skills.intermediate
- Demonstrated awareness of how to function in a team setting.intermediate
- Demonstrated awareness of presentation skills.intermediate
Required Qualifications
- Master's degree / Bachelor's degree and 5 to 9 years of Life Science/Biotechnology/Pharmacology/Information Systems experience. (experience)
- 3+ years of experience in AI/ML system architecture and deployment. (experience)
- Experience with agentic AI frameworks and multi-agent orchestration. (experience)
- Experience in Pharma and Biopharma industry preferred but will consider any healthcare industry experience. (experience)
Responsibilities
- Build and maintain full-stack AI applications, ensuring performance, scalability, and cost-efficiency.
- Design and implement agentic AI systems that autonomously perform complex tasks, leveraging LLMs, multi-agent orchestration, and tool integration.
- Collaborate cross-functionally with data scientists, engineers, and product teams to drive innovation and platform reuse.
- Stay current with the latest trends in generative AI, multi-modal models, and agent frameworks (e.g., LangChain, Langgraph, AutoGen, CrewAI).
- Design, develop, and deploy automation workflows using platforms such as UiPath and Power Automate.
Tags & Categories