Private Equity GenAI Solutions Architect, AWS Private Equity

Are you excited about helping the worlds largest Private Equity firms harness Generative AI to transform how their portfolio companies build operate and scale Were looking for a GenAI Solutions Architect to join the AWS Private Equity team a small high-impact group that works directly with PE firms and their portfolios to accelerate AI adoption and drive measurable business outcomes.

Youll sit at the intersection of business strategy and AI technology. Your customers are PE operating partners CTOs and C-suite executives who are making multi-million dollar bets on AI and they need a trusted technical advisor who can translate GenAI capabilities into real value creation across dozens of portfolio companies.

This isnt a typical SA role. Youll engage across the full PE lifecycle from evaluating AI readiness during technical due diligence to designing scalable GenAI strategies that PE firms can replicate across their entire portfolio. Youll lead hackathons architect production AI systems build compelling demos and help PE firms establish AI as a core value creation lever. Your work will span use cases from AI-powered software development and code generation to document intelligence agentic workflows and industry-specific AI applications.

Youll work with AWS GenAI technologies including Amazon Kiro Amazon Bedrock and Amazon SageMaker along with the full breadth of AWS AI services. What matters most is your ability to connect technology to business outcomes that PE firms care about: faster time to value operational efficiency and competitive differentiation across their portfolios.

Key job responsibilities
- Own the technical AI relationship with PE firms and portfolio company leadership operating as their trusted GenAI advisor
- Design and architect production GenAI solutions using Amazon Bedrock SageMaker Kiro and other AWS AI services with a focus on measurable business outcomes
- Lead scalable repeatable GenAI engagements across PE portfolios including hackathons use case identification workshops AI maturity assessments and business case development sessions
- Support PE firms in technical due diligence by evaluating target companies AI readiness and identifying GenAI value creation opportunities pre- and post-acquisition
- Architect systems leveraging LLMs RAG vector databases agentic workflows and fine-tuning techniques for production workloads
- Build compelling demos and proof-of-concepts that demonstrate ROI for GenAI use cases including software development productivity document intelligence conversational AI and agent-based systems
- Develop scalable GenAI strategies that PE firms can deploy across their portfolio companies (think frameworks not one-offs)
- Participate in PE firm business reviews portfolio reviews and annual planning to align GenAI strategies with investment objectives
- Evangelize AWS GenAI technologies through conferences workshops white papers blog posts and thought leadership
- Create reusable assets (reference architectures code samples best practices) that scale impact beyond individual engagements
- Coordinate with SI partners ISV partners and internal AWS teams to deliver customer outcomes
- Contribute to team growth through hiring coaching and mentoring

- Experience developing deploying and managing AI products at scale
- Experience building complex software systems that have been successfully delivered to customers or experience in developing and deploying LLMs in production on GPUs Neuron TPU or other AI acceleration hardware
- Experience in a customer-facing role engaging with customer executives technologists or partners to solve business problems with advanced technologies
- Masters degree in engineering technology computer science machine learning robotics operations research statistics mathematics or equivalent quantitative field or experience with Machine and Deep Learning toolkits such as MXNet TensorFlow Caffe and PyTorch
- Excellent communication skills with the ability to translate complex AI concepts for both technical and business audiences

- Experience leading the architecture and design (architecture design patterns reliability and scaling) of new and current systems or experience with Machine Learning and Large Language Model fundamentals including architecture training/inference lifecycles and optimization of model execution
- Experience with full software development life cycle including coding standards code reviews source control management build processes testing and operations or experience programming with at least one software programming language
- Knowledge of compliance and security standards across the enterprise IT landscape
- Experience working with or within Private Equity firms Venture Capital or Investment Banking particularly supporting due diligence post-acquisition value creation or technology strategy
- Experience with AWS AI services (Amazon Bedrock SageMaker Kiro) or equivalent cloud AI platforms
- Experience with MLOps/AIDLC workflows for production AI systems including model deployment monitoring and governance
- Track record leading large-scale technical events (hackathons workshops) with 20-100 participants
- Understanding of PE workflows including deal sourcing due diligence portfolio management and value creation planning
- AWS certifications (AI Practitioner ML Specialty Solutions Architect Professional)
- Thought leadership through public speaking technical writing or open-source contributions
- Willingness to travel to customer locations as needed

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