Data And AI Architect

DysrupIT; Manila; On-site; PHP 1,800,000 - 3,000,000; Full time

Job summary

DysrupIT in Manila seeks an experienced Data/AI Architect to lead pre-contract solutioning and delivery, balancing client engagement with hands-on architecture. You’ll influence delivery standards, build reusable assets, and help shape the practice with rapid, enterprise-grade decisions.

The role includes discovery workshops, target-state architectures, PoCs, and production AI systems (Databricks lakehouses, RAG, agents).

Qualifications

• ≈8 years in data/AI engineering and architecture with senior client-facing consulting.
• Databricks lakehouse architecture, Delta Lake, Unity Catalog, Spark/PySpark, and orchestration.
• Strong Python and SQL with data-modelling judgement and English communication for executives.

Responsibilities

• Lead solutioning and pre-sales, shaping technical approaches and discovery.
• Produce target-state architectures, estimates, exclusions and risks.
• Design PoCs and serve as technical peer to client architects and CIOs.
• Own end-to-end architecture, lead delivery, stand-ups and client engagement when needed.
• Deliver Databricks lakehouses and AI systems (RAG, agents, evaluation, prompt engineering).
• Set CI/CD, IaC, testing, observability and cost standards; mentor client engineers.

Skills

Python

SQL

Data modelling

DevOps

MLOps

English communication

Tools

Databricks Lakehouse

Delta Lake

Unity Catalog

Spark/PySpark

Lakeflow

Delta Live Tables

Azure Data Factory

Fabric

ADLS

Azure OpenAI

Entra ID

Job description

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.