Senior Architect - AI​/ML & Agentic Systems

Who we are

Citius Tech - Shaping Healthcare Possibilities.

Citius Tech is a global IT services, consulting, and business solutions enterprise 100% focused on the healthcare and life sciences industry. We enable 140+ enterprises to build a human-first ecosystem that is efficient, effective, and equitable with deep domain expertise and next-gen technology. With over 8,500 healthcare technology professionals worldwide, Citius Tech powers healthcare digital innovation, business transformation, and industry-wide convergence through next-generation technologies, solutions, and products.

Our Purpose

We are shaping healthcare possibilities to make our clients’ businesses successful, which is not just a statement but our purpose, driving us to explore what’s next in healthcare.

Our goal is clear: to make healthcare better for all – more efficient, effective, and equitable. We are investing in people, technology, innovation, and partnerships to create meaningful change. We see technology not just as a tool but as a catalyst that amplifies human ingenuity to solve complex healthcare challenges.

100% healthcare focus | Trusted by 140+ healthcare and life sciences enterprises | 40% of Fortune 500 healthcare enterprises are our clients | #1 Rated as a leader by top analyst firms

Our vision

To inspire new possibilities for the health ecosystem with technology and human ingenuity.

What is in it for you?

You will drive the definition and implementation of best practices for building, testing, and deploying scalable Machine Learning, Agentic AI, and Generative AI solutions.

Responsibilities:

- - Define and implement best practices for building, testing, and deploying scalable AI solutions, with a focus on Machine Learning, Agentic AI, Generative AI models using hyperscaler provided models or open-source models
- Define and implement Agentic Architecture and Design for scalable and production ready solutions
- Infrastructure Management:
Maintain the infrastructure required for machine learning operations, including cloud services, data storage, and computing resources
- Deployment and Automation:
Develop and implement automation tools and frameworks for deploying Machine Learning and Agentic AI models into production environments efficiently and reliably
- Model Versioning and Management:
Establish processes for version control and management of machine learning models, ensuring traceability, reproducibility, and proper documentation
- Monitoring and Maintenance:
Create monitoring systems to track model performance health, and data quality in production. Implement strategies for retraining and updating models as needed
- Collaboration with Data Scientists and Engineers:
Collaborate with data scientists, machine learning engineers, and software developers to streamline the integration of models into applications, ensuring compatibility and scalability.
- Optimization and Scalability:
Optimize machine learning workflows, algorithms, and infrastructure to improve performance, reduce latency, and handle scalability challenges.
- Continuous Integration/Continuous Deployment (CI/CD):
Implement CI/CD pipelines specific to machine learning workflows to automate testing, integration, and deployment processes.
- Troubleshooting and Issue Resolution:
Identify and address issues related to models, data pipelines, or infrastructure promptly to minimize downtime and maintain system reliability
- Documentation and Knowledge Sharing:
Document processes, configurations, and best practices to facilitate knowledge sharing among team members and enable smooth onboarding of new team members
- Stay Updated with Emerging Technologies:
Keep up to date with the latest advancements in AI/ML technologies, and methodologies to continuously improve operational efficiency.
- Cross-functional Communication:
Collaborate with various teams across the organization, including data science, software engineering, operations, and business stakeholders, to align AI/ML activities with business objectives
- Strong leadership skills with experience in leading technical teams.

Experience:

- - 12 - 18 Years

Location:

- - Chennai
- Mumbai
- Pune
- Bangalore

Educational

Qualifications:

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