Cuesta Partners

Solutions Engineer

• Design cloud-native AI and data solution architectures, including reference patterns, data flows, AI/ML workflows, and LLM orchestration that balance scalability, security, cost, and speed to value.
• Translate AI and data architectures into clear diagrams, executive-ready narratives, visuals, and roadmaps for technical and non-technical stakeholders.
• Advise clients on AI strategy, build-vs-buy decisions, governance, and ethical considerations.
• Integrate and orchestrate data across multiple platforms, including cloud data warehouses and lakes (e.g., Snowflake, BigQuery, Databricks) and external APIs.
• Collaborate with ML Engineers and Data Engineers to validate architectural alignment and integration feasibility.
• Conduct architecture reviews and risk assessments; identify and execute course corrections as needed.
• Architect AI solutions that leverage LLMs and RAG patterns to deliver interpretable insights and human-readable outputs from complex model results.
• Mentor junior architects and consultants; contribute to reusable accelerators, templates, and an internal knowledge base.
• Provide technical oversight across multiple client engagements, ensuring architectural consistency, delivery quality, and alignment between business requirements and implemented solutions.
• Provide hands-on guidance to engineering and data teams on API integrations, data pipelines, and AI service connectivity, ensuring solutions are scalable, secure, and maintainable.
• Stay current on emerging AI platforms, LLM tooling, and cloud-based data services, continuously evaluating how they can enhance our integration capabilities.

AI Solutions Architect

Analytics Engineer

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Principal

• Manage and execute comprehensive technology due diligence assessments for M&A transactions.
• Serve as the primary point of contact for private equity clients and deal teams, delivering strategic recommendations.
• Work closely with private equity partners to evaluate technology's role in post-transaction integration.
• Identify potential risks, including cybersecurity vulnerabilities and software scalability issues.
• Stay up to date on the latest trends and advancements in enterprise technology, AI, and digital transformation.
• Support business development initiatives by contributing to thought leadership and engaging in client pitches.
• Continually identify and implement improvements to the delivery process and artifacts.
• Coach and mentor junior team members, fostering a culture of continuous learning.

AI Solutions Architect

Analytics Engineer

Principal – Technology Due Diligence, Private Equity