Presales Solutions Architect - Data, AI and Cloud (Director)
Presales Solutions Architect - Data, AI and Cloud (Director)
JOB SUMMARY
The Presales Solutions Architect Director at Argano plays a vital role in providing strategic technical leadership across our Data, AI and Cloud practices. This role focuses on shaping technically sound, scalable, and differentiated solutions that align business outcomes with modern digital architectures.
The Presales Solutions Architect works closely with sales, delivery leadership, and practice teams to qualify client needs, design end-to-end solutions, support proposals, and present Argano’s capabilities to enterprise clients. This role serves as a senior technical advisor during complex pursuits, ensuring what we sell can be confidently delivered and scaled.
EDUCATION
- Bachelor's degree in a relevant field such as Computer Science, Engineering, Technical, Business, etc. expected.
- Master’s degree or PhD in computer science or software engineering preferred.
EXPERIENCE
- 10+ years of experience in presales, solution architecture, or technical sales roles within a consulting or professional services environment.
- Proven experience designing and implementing large-scale transformation programs, including data modernization, AI adoption, and cloud migration.
- Deep experience leading presales activities such as:
- Client discovery and scoping sessions
- Solution architecture and design
- Effort estimation and delivery approach definition
- Proposal development and executive presentations
- Statement of Work development
- Demonstrated success designing and leading proofs of concept, prototypes, and solution demonstrations.
- Strong presence with senior and executive stakeholders.
- Excellent communication, storytelling, and presentation skills for both technical and non-technical audiences.
- Ability to operate independently, manage multiple pursuits in parallel, and execute with ownership and urgency.
- Demonstrated thought leadership in Data, AI, or Cloud domains. Professional certifications are desired (or expected once on board.)
TECHNICAL SKILLS
AI & Generative AI
- Experience with Generative AI and LLM platforms, including OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Amazon Q, and Google Vertex AI.
- Strong understanding of RAG architectures, vector databases, embeddings, and agentic AI patterns.
- Experience guiding clients through AI readiness assessments, linking AI ambitions to data and platform maturity.
- Familiarity with AI governance, security, and responsible AI considerations.
Data & Analytics
- Deep experience with lakehouse and analytics platforms and tools including Snowflake, Databricks, DBT, Fivetran, Sigma, BigQuery, and Redshift.
- Strong foundation in data engineering and orchestration, including Airflow, AWS Glue, GCP Dataflow, Cloud Composer, and modern ETL/ELT patterns.
- Experience with data governance, quality, metadata management, and data product design.
Machine Learning
- Working knowledge of machine learning techniques and architecture.
- Familiarity with cloud-native ML tooling and MLOps concepts including deployment, monitoring, and lifecycle management.
Cloud & Platform Engineering
- Strong experience with AWS, Azure, and Google Cloud Platform (GCP).
- Expertise in cloud-native architectures, including containers, Kubernetes, and Infrastructure as Code (IaC).
- Experience with cloud and data migrations, including legacy platform modernization.
- Familiarity with observability and performance tooling.
SKILL REQUIREMENTS
- Strategic Vision: Ability to shape presales strategies that drive growth and align with delivery capabilities.
- Solution Architecture & Discovery: Strong whiteboarding, facilitation, and analytical skills.
- Complex Solution Design: Ability to design and communicate multi-platform data, AI, and cloud solutions.
- Executive Communication: Ability to translate complex technical concepts into clear, compelling value narratives.
- Presales Leadership: Strong collaboration with sales and delivery teams to drive successful outcomes.
- Innovation Mindset: Proactively identify new solution patterns, accelerators, and IP.
- Client-Centric Approach: Focus on outcomes, feasibility, and long-term client success.
PARTNER & ECOSYSTEM EXPERIENCE (Preferred)
- Experience leveraging hyperscaler programs and funding opportunities across AWS, Azure, and Google Cloud.
- Experience working with partners such as Snowflake, Databricks or Informatica.