Data & AI Architect

Dysrupit; Makati; On-site; PHP 2,400,000 - 3,400,000; Full time

Job summary

Dysrupit is seeking an experienced Data/AI Architect to lead pre-sales solutioning and delivery. You will shape architectures, perform PoCs and guide end-to-end delivery with hands-on work on Databricks lakehouses and production AI systems.

Expect frequent client engagement, rapid architectural decisions, and mentoring responsibilities as you build reusable patterns. The role blends discovery, architecture, delivery, and team leadership, with a focus on Azure/Microsoft data tooling, generative

Qualifications

• About eight years in data/AI engineering and architecture with design authority and client exposure.
• Databricks lakehouse stack including Delta Lake, Unity Catalog, Spark/PySpark, orchestration.
• Azure/Microsoft stack: Data Factory/Fabric, ADLS, Azure OpenAI; strong Python/SQL.
• Generative AI: production RAG, agents, evaluation, prompt engineering and tool use.
• Strong English for executive proposals and presentations.

Responsibilities

• Shape technical approaches, run discovery workshops and craft target-state architectures.
• Design PoCs, prepare estimates, exclusions, risks and defensible cost assumptions.
• Own end-to-end architecture, lead delivery, and mentor client engineers.
• Deliver Databricks lakehouses and production AI systems (RAG, agents, evaluation).
• Set CI/CD, IaC, testing, observability and cost standards; turn delivery into reusable assets.
• Contribute to Frontier Academy and keep recommendations current across Databricks, Microsoft and Anthropic.
• Help shape and potentially lead a small delivery team including recruitment.

Skills

Data engineering

AI architecture

Client-facing

Python

SQL

Data modeling

MLOps

DevOps

CI/CD

English communication

Tools

Databricks lakehouse

Delta Lake

Unity Catalog

Spark/PySpark

Delta Live Tables

Azure Data Factory

Fabric

ADLS

Azure OpenAI

Entra ID

Power BI

Job description

JOB SUMMARY

The architect will lead both pre-contract technical solutioning and subsequent delivery, preserving continuity from proposal to production. Joining a small, senior practice means early client exposure, fast architectural decisions, hands-on implementation and direct influence over delivery standards and reusable assets. It also means varied, ambiguous work and occasionally creating the playbook; candidates seeking a tightly defined remit may not find the role suitable. Time is split approximately equally between client engagement and delivery, flexing with the pipeline. Typical work includes discovery workshops, target-state architecture, proposal estimates, code review, building a retrieval-augmented vertical slice, client enablement, steering-committee presentations and converting lessons into reusable patterns.

JOB RESPONSIBILITIES:

Solutioning and pre-sales

• Shape technical approaches, challenge problem statements and facilitate discovery workshops.
• Produce target-state architectures, build sequences, proposal assumptions, exclusions, risks and defensible estimates.
• Design four-to-six-week proofs of concept and serve as technical peer to client architects, data leaders and CIOs.

Delivery and hands-on architecture

• Own end-to-end architecture and, where required, lead delivery, scope, stand-ups and client technical
• Remain hands-on, implementing demanding components and reference solutions.
• Deliver Databricks lakehouses, including medallion layers, Unity Catalog, Delta Lake, ingestion and orchestration.
• Build production generative AI systems covering RAG, agents, evaluation, prompt/context engineering, cost and latency.
• Set CI/CD, infrastructure-as-code, testing, observability and cost standards; mentor client engineers and manage production readiness and handover.

Practice capability and intellectual property

• Turn delivery experience into reference architectures, accelerators, templates and estimation models.
• Contribute to Frontier Academy and maintain current recommendations across Databricks, Microsoft and Anthropic.
• Help shape and eventually lead a small delivery team, including recruitment.

JOB QUALIFICATIONS:

Must Have:

• About eight years in data/AI engineering and architecture, including three years with substantive design authority and senior client-facing consulting exposure.
• Databricks: lakehouse architecture, Delta Lake, Unity Catalog, Spark/PySpark, Lakeflow or Delta Live Tables, orchestration, performance and cost optimisation.
• Azure/Microsoft: Data Factory or Fabric, ADLS, Azure OpenAI or AI Foundry, Entra ID and networking
• Generative AI: production RAG, vector stores, agents/tool use, evaluation, guardrails and prompt/context engineering, including Claude or an equivalent frontier model.
• Strong production Python and SQL; sound data-modelling judgement across dimensional, data vault and wide denormalised approaches.
• DevOps/MLOps fundamentals: version control, CI/CD, infrastructure as code, containers and monitoring.
• Excellent written and spoken English for executive proposals, decision records and presentations.

Desirable:

• Databricks Professional or Azure Solutions Architect Expert certification.
• Big Four, global systems integrator or specialist consultancy experience, including bids, statements of work and estimation.
• Applied responsible AI governance and delivery experience in financial services, retail or travel.
• Experience with Australian/APAC clients, Snowflake, dbt, Power BI or Fabric, and mentoring small engineering teams.