Chief Technologist

Chief Technologist

This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2-3 days per week from an HPE office.

**Who We Are**:
**HPE Services **is our innovative IT services organization. It provides the expertise to advise, integrate, and accelerate our customers’ outcomes from their digital transformation. Our teams collaborate to transform insight into innovation. In today’s fast paced, hybrid IT world, being at business speed means overcoming IT complexity to match the speed of actions to the speed of opportunities. Deploy the right technology to respond quickly to market possibilities. Join us and redefine what’s next for you.

**What you’ll do**:
We are seeking an experienced Cheif Technologist with a strong background in Machine Learning Development Environments, MLOps, and Pachyderm to join our dynamic team. In this role, you will collaborate closely with our clients to design, implement, and optimize ML workflows, ensuring seamless integration of ML models into production environments.

Senior technologist who would bring in valuable expertise, guiding us through technical challenges.

Apart from being the Tech SPOC for our conversations with Geo’s and BU, the below mentioned deliverables will be part of his/her responsibilities.

Delivery Assurance

Develop and implement comprehensive delivery assurance strategies for professional services in AI and data, laying foundation for the successful and timely completion of projects.

Monitor and assess project lifecycles, identifying potential bottlenecks and implementing effective mitigation strategies to ensure client satisfaction.

Reference Architecture:
Establish and maintain a standardized reference architecture framework, providing guidance for project implementations and ensuring consistency in deliverables.

Technical Strategy:
Formulate a client-centric technical strategy for RPS and Field, aligning technological initiatives with client requirements and industry best practices.

Generate repeatable IP’s:
Develop and maintain repeatable and reusable packages for HPC and AI solutions, fostering operational efficiency and accelerated project delivery.

Emerging Technology:
Stay informed about the latest developments in AI and data technologies, evaluating their relevance and potential impact on client services, and recommend their incorporation into service offerings.

Assess and implement emerging technologies to enhance the quality and effectiveness of AI and data services for clients.

Coaching:
Provide professional guidance and coaching to team members in delivering AI and data professional services, fostering skill development and promoting excellence in client engagement.

Offer tailored coaching to ensure the team's understanding of client requirements and effective communication of technical solutions.

Risk Assessment and Mitigation for Large Deal Management:

- Identify and mitigate technical risks associated with large deal management and delivery, ensuring the successful execution of complex AI and data projects in both remote and field environments.
- Collaborate with cross-functional teams to develop comprehensive risk management strategies and contingency plans for large-scale project delivery
- Identify and manage technical dependencies within client projects, ensuring effective coordination and communication among team members and clients.
- Implement strategies to mitigate risks associated with technical dependencies, ensuring seamless integration and delivery of AI and data professional services.

Quality Assurance and Optimization for Large Deal Delivery:
Establish comprehensive quality assurance protocols for AI and data service delivery in l projects, focusing on maintaining technical excellence and performance standards.

Implement technical optimizations and improvements to enhance service quality and ensure the successful delivery of projects in diverse operational environments.

**What you need to bring**:
**Qualifications**:

- Bachelor’s/master’s degree in computer science, Information Technology, or a related field.
- Minimum of 12+- years of **experience in managing machine learning projects**. Strong understanding of operating systems and distributed systems. **Experience in designing and building architecture and systems engineering for large-scale deployments comprising different components.**:

- Demonstrated leadership skills and the ability to drive various building blocks of AI/ML stack.
- Previous experience in the design and implementation of large-scale, distributed systems.
- Experience with machine learning and artificial intelligence platforms, including model deployment and integration.
- Excellent communication and presentation skills with the ability to convey complex technical concepts to non-technical stakeholders.

**Additional Skills**:
Artificial Intelligence Technologies, Cross Domain Knowledge, Data Engineering, Data Science, Design Think