Client Engineering - Ecosystem

Introduction

At IBM Global Sales, we bring together innovation, collaboration, and expertise to help clients solve their most complex business challenges. Working across industries and geographies, you'll partner with colleagues, clients, and partners to co-create solutions that drive digital transformation and lasting impact.Success in Global Sales is built on curiosity, empathy, and collaboration. You'll connect technical understanding with strong people skills, building trusted relationships and shaping solutions that improve business and society. With world-class onboarding, continuous learning, and a supportive culture, IBM offers the tools and opportunities to grow your career. Join us and be part of a global team that's passionate about driving innovation and making a difference.

Your role and responsibilities

Your role is a Sales Engineer as part of IBM Technology sales organization. This is a customer facing sales role with sales target.

• Sales-Driven POC Development: Develop Proof of Concepts (POCs) and "Proof of Experiences" (PoX) that do more than just work-they sell. You will validate feasibility while highlighting the ROI and competitive advantages of IBM's AI and Automation portfolios.
• Strategic Collaboration: Partner with Account Executives and Technical Sales Leaders to identify "win themes" for each engagement. You will lead cross-functional squads to ensure our technical delivery aligns perfectly with the client's budget and decision-making criteria.
• Solution Implementation & Deployment: Oversee the rapid deployment of AI solutions, ensuring that even at the pilot stage, the architecture is robust and ready for production-scale investment.
• Conversion Optimization: Continuously monitor and fine-tune the performance of complex solution involving AI and Automation. You will provide the technical evidence required to overcome client objections and shorten the sales cycle.
• Technical Client Leadership: Act as the trusted technical advisor for C-suite stakeholders. You will bridge the gap between complex algorithmic improvements and the business outcomes that drive client spend.
• Scaling Success: Document architectures and design decisions to create "repeatable patterns." Your goal is to build once and sell many times, contributing to internal playbooks that allow IBM to scale Technology sales in your respective territory.
• Innovation for Competition: Stay ahead of the curve on AI and Automation trends to ensure IBM's offerings always remain the superior choice in a competitive marketplace.

• Value Engineering & ROI Analysis: Ability to translate technical features (e.g., latency, model accuracy) into business outcomes (e.g., cost savings, revenue growth, or risk mitigation).
• Strategic "Win Theme" Identification: Skill in analyzing a client's business landscape to identify the specific technical "hooks" that will beat a competitor and secure a budget.
• Sales Cycle Management: Understanding of the enterprise sales funnel-knowing when to dive deep into technicals and when to push for a technical win to move the deal to the procurement stage.
• Entrepreneurial Resourcefulness: A "scrappy" mindset to navigate internal IBM silos and assemble the right squad or resources to deliver a pilot under tight 4-to-6-week deadlines.
• Discovery & Qualification: Proficiency in asking the right questions to qualify an opportunity, ensuring you spend time on POCs that have a high probability of conversion.

• Executive Presence: The confidence and clarity required to present to C-suite stakeholders, maintaining IBM's position as a "Trusted Advisor."
• Technical Storytelling: The ability to weave a narrative around a Proof of Experience (PoX) that captures the client's imagination and makes the "future state" feel achievable.
• Active Listening & Objection Handling: Skill in hearing a client's technical hesitation and reframing it as a solution opportunity, using evidence to dismantle roadblocks in real-time.
• Complex Simplification: Translating sophisticated AI concepts (like Agentic AI, retrieval-augmented generation or foundation model fine-tuning) into simple, impactful language for non-technical decision-makers.

• IBM Portfolio Mastery: Expert-level knowledge of watsonx.Orchestrate, watsonx.ai, watsonx.data, and watsonx.governance, along with IBM's Automation suite (e.g., Instana, Turbonomic, or Cloud Pak for Business Automation).
• Technical Architecture & Engineering: Proficiency in Python, RAG (Retrieval-Augmented Generation) patterns, and prompt engineering. You should be able to build and optimize models that are enterprise-grade.
• Hybrid Cloud Knowledge: Familiarity with Red Hat OpenShift, Public Cloud and how AI workloads scale across multi-cloud environments.
• Rapid Prototyping: Speed is a skill. You must be adept at building "good enough for pilot" solutions that are architecturally sound enough to scale into production.