Automation Technology Sales Engineer - Partner

Introduction

A Technology Sales Engineer role (what we internally call a, 'Partner Technical Specialist') within Automation means working for a leader in AI-Powered products. Envision helping clients create a world with less repetitive work and more innovative decisions. Less unplanned downtime and more proactive insight. And less waiting on systems... So that their employees can invest more time on the work they love. Join us and co-create with clients on solutions that makes people more productive and improves business performance, so that they can change the world at a scale not previously possible.

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.

• Collaborate with sales and clients to identify operational challenges (e.g., manual interventions, security issues, unreliable deployments).
• Convert these findings into high-level architectural strategies that incorporate AI-driven automation, DevSecOps principles, and SRE best practices.
• Align on desired outcomes and ROI by leading requirement-gathering sessions with both technical and business stakeholders.

• Prepare and deliver tailored demos showcasing how AI-based automation addresses specific pain points (e.g., anomaly detection, self-healing).
• Plan and execute POCs with clearly defined success criteria and actionable next steps.
• Proactively identify solution gaps and risks, steering clients toward best practices.

• Show how AI-powered insights can enhance observability, alerting, and incident management, reducing MTTD and MTTR.
• Provide high-level guidance on migrating or optimizing workloads in major cloud platforms (AWS, Azure, GCP).
• Illustrate the value of Infrastructure as Code (IaC) and outline best practices for containerization, including Kubernetes and OpenShift, to ensure consistency, scalability, and streamlined operations.
• Advise on suitable AI Ops tools (e.g., monitoring, log analysis) aligned with client needs and existing tech stacks.

• Develop technical proposals and solution overviews in partnership with sales, ensuring alignment between commercial and technical objectives.
• Contribute to RFP/RFI responses, clearly articulating how proposed solutions meet client requirements.
• Serve as a trusted advisor, bridging client objectives with the solution's technical roadmap.

• Collaborate with Product, Engineering, and Customer Success teams to ensure alignment on features, roadmaps, and deployment.
• Maintain strong client relationships, acting as the main technical contact throughout the sales cycle.
• Partner with external technology providers or integrators to deliver comprehensive, end-to-end solutions.

• Stay current on trends in DevSecOps, SRE, and AI Ops, evaluating new tools or methodologies to enhance client solutions.
• Share insights and best practices through workshops, webinars, or whitepapers, building market credibility.
• Provide feedback on evolving client needs to guide future product and service enhancements

1. DevSecOps & SRE Fundamentals
   
   
   • Familiarity with continuous integration (CI), continuous delivery (CD), and automated security checks (e.g., SAST, DAST).
   • Understanding of SRE principles (SLOs, SLIs, error budgets) and how they inform observability, incident management, and reliability metrics.
2. Cloud & Container Orchestration
   
   
   • Hands-on experience or strong conceptual knowledge of AWS, Azure, or GCP (at least one current certification on a major cloud provider is required).
   • Proficiency in containerization (Docker) and orchestration platforms like Kubernetes or OpenShift.
3. AI Ops & Automation Insight
   
   
   • Basic familiarity with AI-driven solutions (e.g., anomaly detection, predictive maintenance) that reduce manual intervention and streamline operations.
   • Ability to recommend suitable AI Ops tools for monitoring, logging, or automatic remediation.
4. Technical Solution Design & Advisory
   
   
   • Proven ability to translate client challenges (manual tasks, security gaps, etc.) into high-level architectures, incorporating DevSecOps and SRE best practices.
   • Comfort discussing Infrastructure as Code (e.g., Terraform, CloudFormation) and architecting scalable, secure deployments.
5. Client-Facing & Collaborative Experience
   
   
   • Strong presentation and communication skills, capable of delivering tailored demos and guiding technical Proof-of-Concepts (POCs).
   • Demonstrated success working cross-functionally (e.g., with sales, product, and engineering) to align on proposals and deployment plans.
6. Proposal Development & Documentation
   
   
   • Experience contributing to RFPs, RFIs, or similar technical documentation, clearly outlining solution capabilities and alignment with business goals.
   • Ability to develop concise, persuasive technical proposals and solution roadmaps.

• Advanced Cloud Credentials
  
  
  • Additional or higher-level certifications (e.g., AWS Solutions Architect Associate, Azure Administrator Associate, Google Cloud Associate Engineer).
• Container & Orchestration Certifications
  
  
  • Familiarity with credentials like the Certified Kubernetes Administrator (CKA) or Red Hat's OpenShift certifications.
• DevSecOps or Security Training
  
  
  • Completion of recognized courses or certifications (e.g., DevOps Institute) indicating a deeper grasp of secure development practices.
• AI Ops & Observability
  
  
  • Experience leveraging AI-driven tools for monitoring and incident management, plus comfort with observability stacks (e.g., Prometheus, Grafana).
• Practical Automation & Incident Response
  
  
  • Exposure to infrastructure-as-code frameworks (Terraform, CloudFormation) and chaos engineering or advanced troubleshooting methods that enhance system resilience.