Ashish Saraf

Ashish Saraf is an Automation Presales Consultant and Solution Architect at IBM, specializing in automation solutions and cloud technologies. He has a strong background in information technology, particularly in areas such as software development, network management, and cloud services. Saraf's expertise spans various technologies including Wide Area Networks (WAN), Software-Defined Wide Area Networks (SD-WAN), and public cloud platforms like Azure and AWS.

Professional Background

• Current Role: As an Automation Presales Consultant at IBM, Saraf engages with clients to understand their automation needs and provides tailored solutions that leverage IBM's technology offerings.
• Previous Experience: He has accumulated over 8 years of experience in the IT industry, working in roles that emphasize sales engineering and technical consulting. His career includes significant positions where he has contributed to digital transformation initiatives and the implementation of complex IT solutions.

Skills and Expertise

• Technical Skills: Saraf is skilled in various domains such as:
  • Network Technologies: Expertise in WAN, SD-WAN, and Unified Communications.
  • Cloud Services: Proficient in deploying solutions on platforms like AWS and Azure.
  • Automation: Focused on automating business processes to enhance efficiency and reduce operational costs.

Education

Saraf holds a Bachelor’s degree in Computer Science, which laid the foundation for his technical skills and understanding of software engineering principles.

Professional Philosophy

Saraf is known for his consultative approach, helping organizations navigate their automation journeys by aligning technology with business objectives. His ability to blend technical knowledge with strategic insights makes him a valuable asset in presales scenarios where understanding client needs is crucial.

Through his work at IBM, Ashish Saraf continues to contribute significantly to the field of automation and cloud solutions, helping businesses leverage technology for improved operational performance.