Senior Consultant/Principal - Data & AI Solution Architect

Slalom Build; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Slalom Build in Singapore is hiring a Solution Architect for Data & AI solutions. The role involves defining scalable architecture, working with senior client stakeholders, and driving digital transformation through data and AI technologies.

The ideal candidate has 5-12+ years of experience and strong expertise in cloud platforms like AWS, Azure, and GCP. Excellent client engagement skills and hands-on experience with ML pipelines are essential for success in this position.

Qualifications

• 5-12+ years of experience in data engineering, data architecture, or AI/ML solution delivery.
• Expertise across cloud platforms and modern data platforms.
• Hands-on experience building ML pipelines in production-grade systems.

Responsibilities

• Define and design end-to-end Data & AI architectures.
• Architect modern data platforms and guide implementation.
• Act as a trusted advisor to client stakeholders.

Skills

Data engineering

Data architecture

AI/ML solution delivery

Client-facing skills

Programming (Python)

Cloud platforms (AWS, Azure, GCP)

MLOps practices

Tools

Snowflake

Databricks

BigQuery

Redshift

Synapse

Airflow

dbt

Job description

About Slalom

Slalom is a global, human-centric business and technology consulting firm. We specialise in partnering with organisations that aspire to excellence, helping them tackle complex challenges and achieve transformative results through strategy, technology, and business transformation services. By prioritising people, Slalom creates a unique consulting experience, with a team of strategists and engineers delivering practical, end-to-end solutions that drive impactful outcomes for our clients. We empower people and organisations to dream bigger, move faster, and build better tomorrows for all.

About the Role

As a Solution Architect, Data & AI at Slalom, you will operate at the intersection of business strategy, data architecture, and AI engineering. You’ll work closely with senior client stakeholders and delivery teams to co‑create modern data and AI solutions that accelerate digital transformation and deliver measurable business outcomes. Your expertise will shape scalable, cloud‑native platforms powering analytics, machine learning, and Generative AI use cases across industries. You guide clients from experimentation to production‑scale AI adoption, ensuring governance, scalability, and operational excellence - across AWS, Azure, and GCP ecosystems.

What You’ll Do

• Define and design end‑to‑end Data & AI architectures, translating business requirements into scalable, secure, cloud‑native solutions
• Architect modern data platforms and guide implementation of ML & GenAI pipelines, ensuring seamless integration between data, AI services, and business applications
• Establish MLOps and GenAI solution patterns - including CI/CD pipelines, RAG architectures, embedding pipelines, and LLM integrations - for robust, production‑grade AI systems
• Act as a trusted advisor to client stakeholders, leading workshops, technical assessments, and translating complex technology into clear business outcomes and value narratives
• Guide engineering teams for delivery quality and governance, mentoring engineers and ensuring solutions meet security, compliance, and regulatory requirements
• Contribute to Slalom’s Data & AI capability development, accelerators, and reusable assets, while providing thought leadership internally and externally

What You’ll Bring

• 5-8 years (Senior Consultant) or 8-12+ years (Principal) of experience in data engineering, data architecture, or AI/ML solution delivery, with a proven track record designing and delivering enterprise‑scale Data & AI solutions
• Strong expertise across cloud platforms (AWS, Azure, GCP) and modern data platforms (Snowflake, Databricks, BigQuery, Redshift, Synapse)
• Hands‑on experience building ML pipelines, applying MLOps practices, and implementing GenAI solution patterns (embeddings, vector databases, RAG, LLM integration) within production‑grade systems
• Deep knowledge of data modeling, ingestion, transformation, serving patterns, and familiarity with streaming frameworks (Kafka, Kinesis, Pub/Sub)
• Strong programming background (Python preferred), experience with orchestration tools (Airflow, dbt), CI/CD practices, and leading technical workstreams for large programmes
• Excellent client‑facing and stakeholder engagement skills, structured problem‑solving abilities, and experience mentoring engineers and promoting best practices in data engineering, AI, and platform design

Nice to Have

• Experience in regulated industries (banking, financial services, government) and familiarity with Responsible AI, governance, and compliance frameworks
• Experience with AI platforms (SageMaker, Azure ML, Vertex AI), containerization, and platform engineering (Kubernetes, Terraform)
• Contributions to pre‑sales, solutioning, or go‑to‑market development