Are you a strategic technical leader who measures success by the measurable business outcomes your customers achieve? We are seeking a Principal Solutions Architect within our Customer Success organization to serve as the trusted technical advisor to our most strategic enterprise customers adopting generative AI inference at scale through AWS Mantle and Amazon Bedrock. In this role, you will own the post-sales customer journey end-to-end-from initial adoption through production optimization and value realization-driving clarity in high-ambiguity environments where customers' AI strategies, operating models, and success criteria may not yet be defined. You will work backwards from customer outcomes to architect solutions, remove adoption barriers, and ensure customers achieve transformational business results.

- Serve as the primary strategic technical advisor to customers' senior and executive stakeholders, shaping their long-term AI inference strategies and guiding them from proof-of-concept through production at scale on AWS Mantle

- Own customer transformation health end-to-end-proactively identifying adoption barriers, architecting solutions to overcome them, and driving measurable value realization (latency improvements, cost optimization, time-to-production)

- Operate with complete independence in deeply ambiguous engagements where the customer's business objectives, technology strategy, and success criteria are not yet defined-driving clarity and creating the path forward

- Influence AWS product and engineering roadmaps by synthesizing customer feedback patterns, articulating unmet needs, and championing the customer perspective with internal leadership

- Establish scalable customer success methodologies, frameworks, and playbooks that accelerate adoption of Mantle's inference capabilities across the broader customer base

Key job responsibilities

As a Principal Solutions Architect on the Customer Success side of Mantle, you will be the connective tissue between our customers' most ambitious generative AI goals and the production-ready reality of operating AI inference at enterprise scale. Your success is measured not by designs delivered, but by customer outcomes achieved-production workloads launched, performance targets met, and business value realized.

- Own structured success planning for strategic customer accounts, including executive business reviews, adoption milestones, and proactive health monitoring to ensure customers achieve their AI inference goals on Mantle and Amazon Bedrock

- Architect production-ready inference solutions leveraging Mantle's distributed engine, Zero Operator Access security model, and OpenAI-compatible APIs-optimizing for customer-specific requirements around latency, throughput, cost, and compliance

- Lead deep-dive technical engagements to resolve complex production challenges, including model performance tuning, capacity planning, multi-region deployment strategies, and integration patterns with customers' existing ML pipelines

- Gather, decompose, and prioritize customer feedback across many accounts and use cases-translating pain points into actionable product roadmap inputs for Mantle engineering teams, including PR/FAQ creation and feature prioritization influence

- Create and evangelize reference architectures, best practices, and reusable patterns for AI inference at scale; lead workshops, publish technical content, and mentor other Solutions Architects to raise the bar across the Customer Success organization

About the team

The AWS Mantle Customer Success team ensures that enterprise customers successfully adopt, scale, and realize measurable business value from generative AI inference on Amazon Bedrock. We sit at the intersection of our customers' ambitions and Mantle's technical capabilities-working backwards from business outcomes to deliver production-ready AI solutions. Our Zero Operator Access architecture means customers can trust that no person-whether from AWS, a customer, or a model provider-can ever access their inference data, and we help them understand and operationalize that trust in their environments.

- We are customer-obsessed, measuring our success by production workloads launched, adoption velocity, and quantifiable business impact our customers achieve

- We partner deeply with Mantle engineering, product, and go-to-market teams-serving as the voice of the customer and driving feedback loops that shape the platform's evolution

- We foster a collaborative, inclusive environment where diverse perspectives drive better customer outcomes-and where creative problem-solving is valued over rigid process

- We support customers across industries adopting models from OpenAI, Anthropic, DeepSeek, Google, Mistral, NVIDIA, and more-each with unique scale, compliance, and performance requirements

- We believe the best customer experiences come from teams that are curious, empathetic, and relentless about removing friction from the path between ambition and production

BASIC QUALIFICATIONS

- 10+ years of managing a technical team of solution architects, sales engineers or similar technical roles experience

- 8+ years of cloud architecture and solution implementation experience

- Experience working with, presenting to and influencing senior executives up to VP level

- Experience managing and quantifying improvements in customer experience or value for the business resulting from research outcomes

- Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience

PREFERRED QUALIFICATIONS

- Master's degree in computer science, machine learning, engineering, or related fields, or PhD

- Deep expertise in generative AI, ML inference systems, or model-serving architectures (e.g., Amazon Bedrock, SageMaker, vLLM, TensorRT)

- Experience designing customer success frameworks, adoption playbooks, or structured value realization methodologies for emerging technology platforms

- Proven thought leadership-publishing white papers, presenting at industry conferences, or contributing to open-source projects in AI/ML

- Experience with security-first architectures including zero-trust, confidential computing, or data sovereignty requirements in regulated industries (financial services, healthcare, government)

- Ability to synthesize complex, cross-customer feedback into strategic product recommendations that influence engineering roadmaps