Pre-Sales Solution Architect - Data & AI

What you bring:

• 8+ years in solution architecture, data architecture, or pre-sales, with at least 4 years specifically designing enterprise data platforms and analytics solutions.
• Deep, hands-on architectural expertise in at least two of: Databricks, BigQuery, Redshift, Microsoft Fabric — including workload sizing, cost modeling, and migration strategy.
• Deep expertise in designing and presenting end-to-end enterprise solutions using cloud platforms like AWS, Azure, and GCP, as well as emerging technologies in data and AI.
• Proven design experience with batch and streaming pipelines using tools such as dbt, Airflow, Fivetran, Spark, Kafka, Kinesis, Flink, or equivalents.
• Working knowledge of lakehouse and data mesh principles, open table formats (Delta, Iceberg, Hudi), and the trade-offs between centralized and federated data architectures.
• Practical experience designing AI/ML and GenAI data foundations — feature stores, vector databases, RAG pipelines, embedding strategies, and MLOps integration points
• Skilled at delivering innovative yet practical solutions that are secure, reliable, and scalable for real-world applications.
• Comfortable working closely with engineering, business teams, and cloud channel partners to shape and align solutions with strategic customer goals.
• Experienced in requirements gathering, RFP/RFI responses, and delivering compelling technical presentations to both executive and technical stakeholders.
• Strong communication and interpersonal skills, with the ability to simplify and clearly explain complex technical concepts to diverse audiences.
• Willingness to travel up to 30% for client workshops, technical discovery sessions, and stakeholder engagements.

Addepto is a leading AI consulting (addepto.com/ai-consulting/) and data engineering (addepto.com/data-engineering-services/) company that builds scalable, ROI-focused AI solutions for some of the world's largest enterprises and pioneering startups, including Rolls Royce, Continental, Porsche, ABB, and WGU. With an exclusive focus on Artificial Intelligence and Big Data, Addepto helps organizations unlock the full potential of their data through systems designed for measurable business impact and long-term growth.

The company's work extends beyond client engagements. Drawing from real-world challenges and insights, Addepto has developed its own product - ContextClue - and actively contributes open-source solutions to the AI community. This commitment to transforming practical experience into scalable innovation has earned Addepto recognition by Forbes as one of the top 10 AI consulting companies worldwide.

As part of KMS Technology, a US-based global technology group, Addepto combines deep AI specialization with enterprise-scale delivery capabilities—enabling the partnership to move clients from AI experimentation to production impact, securely and at scale.

We're seeking a seasoned Pre-Sales Solution Architect with deep data architecture expertise to shape high-impact data and AI solutions for prospective and existing clients. Working closely with Sales, Data Engineering, and AI/ML practice leads, you'll own the technical narrative for opportunities centered on modern data platforms, analytics modernization, data governance, and AI-ready data foundations.

You'll serve as a trusted advisor on what it actually takes to move clients from fragmented data estates to lakehouse, data mesh, or domain-aligned architectures that power analytics, operational intelligence, and production AI. Your focus will span enterprise and high-growth clients — including large ISVs, healthcare innovators, and digital-native businesses — primarily in the U.S. and Europe, many of whom are consolidating data platforms, migrating off legacy warehouses, standing up AI/ML capabilities.

This is a dynamic, client-facing role for someone who can move fluently between a CDO's strategy conversation and a data engineering whiteboard.

,[Lead Data-Centric Discovery: Run technical discovery focused on data estates, source systems, latency and quality requirements, analytics maturity, and AI readiness — translating findings into target-state architectures., Design Modern Data Platforms: Produce reference architectures spanning ingestion, storage, transformation, semantic, and consumption layers on Snowflake, Databricks, BigQuery, Redshift, or Microsoft Fabric — including lakehouse, medallion, data mesh, and event-driven patterns., Architect for AI: Design feature stores, vector stores, retrieval pipelines, and ML/LLM data foundations that move clients from experimentation to production GenAI and predictive use cases., Build Credible PoCs: Scope and deliver high-signal proofs around data migration, real-time pipelines, governed self-service analytics, or RAG/agentic patterns that demonstrate value in weeks, not quarters., Own the Technical Narrative: Lead RFx responses, SOWs, and proposals for data and AI opportunities — including sizing, sequencing, and risk framing for multi-phase modernization programs., Be the Face of Innovation: Present at executive briefings, architecture deep dives, and solution workshops, earning trust with data leaders (CDO, CDAO, VP Data, Head of Analytics) and engineering audiences alike., Govern by Design: Embed data governance, lineage, quality, and privacy (HIPAA, GDPR, CCPA, SOC 2) into every blueprint — not as an afterthought, but as a first-class design constraint., Lead and Mentor: Provide technical leadership across the pre-sales and data practice, partnering with delivery leads on clean handoffs and uplifting peers on modern data.] Requirements: Data science, AI, Python, Cloud, GenAI, LLM, Machine Learning, Data engineering, Big data, Pre-sales, Presales, Databricks Tools: Jira, GitLab, Agile, Scrum. Additionally: Private healthcare, Multisport card, Referral bonus, MyBenefit cafeteria, International projects, Flat structure, Paid leave, Training budget, Language classes, Team building events, Small teams, Flexible form of employment, Flexible working hours and remote work possibility, Sport subscription, Free coffee, Shower, Startup atmosphere, No dress code, In-house trainings.