Data and AI Technology Engineer

Introduction
A Technology Sales Engineer role (what we internally call a ‘Brand Technical Specialist’) within IBM’s Data & AI brand means accelerating enterprises’ success by improving their ability to understand their data. It means providing solutions that enable people across organizations in multiple roles the ability to turn data into actionable insights without having to wait for IT. And it means selling multi-award winning software and world-class design practices that enables business analysts to ask new questions. The answers to which are literally shaping the future and changing the world.

Excellent onboarding and an industry leading learning culture will set you up for positive impact and success whilst ongoing development will advance your career through an upward trajectory. Our sales environment is collaborative and experiential. Part of a team you’ll be surrounded by bright minds and keen co-creators – always willing to help and be helped – as you apply passion to work that will compel our clients to invest in IBM’s products and services.

Your Role and Responsibilities

As a Brand Technical Specialist you’ll work closely with clients to develop relationships understand their needs earn their trust and show them how IBM’s industry leading solutions will solve their problems whilst delivering value to their business.

Your primary responsibilities will include:

– Client Strategy Design: Creating client strategies for Data & AI infrastructure.
– Solution Definition: Defining IBM Data & AI solutions that enhance technology stacks.
– Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs ensuring alignment with customer requirements and expectations.
– Credibility Building: Establishing credibility and trust to facilitate the closure of intricate Cloud tech deals.

Required Technical and Professional Expertise

Expertise in Generative AI and LLMs: Deep understanding of GenAI models including transformers with experience in applying these models to solve business challenges.
Data Preparation for LLMs: Proficiency in data curation tokenization and preprocessing with expertise in tools like Hugging Face Transformers or TensorFlow for preparing data and training LLMs.
AI Model Lifecycle Management: Familiarity with MLOps practices including model versioning monitoring and retraining to ensure ongoing model performance.
Cloud and Containerization Skills: Experience deploying AI solutions on cloud platforms (IBM Cloud AWS Azure) using containerized environments such as OpenShift or Kubernetes.
Sales and Consultative Skills: Ability to engage with clients identify GenAI use cases and translate complex AI technologies into valuable business outcomes using watsonx solutions.

Preferred Technical and Professional Expertise

Advanced NLP and Language Model Knowledge: Expertise in NLP tasks like text summarization question-answering and text generation with experience using frameworks like Hugging Face or LangChain.
Familiarity with IBM’s AI Ecosystem: Knowledge of IBM’s AI tools including Cloud Pak for Data and watsonx.governance and how they support GenAI and LLM solutions.
Prompt Engineering and Customization: Skills in prompt engineering and customizing LLMs to align with specific client needs for improved model accuracy and efficiency.