AI Solution Architect

PwC is hiring an AI Solution Architect in Singapore, Singapore. Level rates it ; you can apply on PwC.

Level's read on this job

On Level's scale, this solutions architect role is Works on AI ●●●○: the daily work is on AI products, without building the model.
PwC mentions visa sponsorship in this posting.
Tools and skills the posting cites include OpenAI, Claude and Anthropic.
Level classifies it as a senior role.
Level lists 3,700+ other open roles at PwC.

AI in this role

AI Solution Architect leads client pre-sales, technical discovery, and AI architecture implementation across various enterprise platforms.

OpenAIClaudeAnthropicCopilotMistralLlamaLangChainLlamaIndexLangGraphCrewAIAutoGenAnthropic API+17

prompt-engineeringragllm-integrationai-agentsai-safetyapi-developmentdata-engineeringmulti-agent-frameworksvector-databasesai-governance

Line of Service

Assurance

Industry/Sector

Not Applicable

Specialism

Risk

Management Level

Manager

Job Description & Summary

At PwC, we help clients build trust and reinvent so they can turn complexity into competitive advantage. We’re a tech-forward, people-empowered network with more than 364,000 people in 136 countries and 137 territories. Across audit and assurance, tax and legal, deals and consulting, we help clients build, accelerate, and sustain momentum. Find out more at www.pwc.com.

Core Responsibilities

Lead technical solutioning in client pre-sales and discovery across all sectors — translating business problems into AI architectures (RAG pipelines, agentic workflows, SDLC automation, data platforms, model risk frameworks)
Own the technical sections of client proposals and engagement scoping documents, including architecture diagrams and implementation sequencing
Build and maintain reusable accelerators and demo assets deployable within 48 hours for client workshops across all use cases
Lead or co-lead technical delivery on AI pilot engagements from architecture through to production handover
Stay current on the AI tooling landscape — with particular depth in the Anthropic/Claude ecosystem — and translate into client-relevant recommendations
Advise on AI governance and responsible AI design, particularly for FS clients subject to MAS regulatory scrutiny on model risk, explainability, and audit trails

Must-Have Skills

Python proficiency — LLM integration, API development, data engineering, and automation scripting
Cloud AI platforms — Azure OpenAI Service, AWS Bedrock, or GCP Vertex AI (at least one in depth)
LLM orchestration — LangChain, LlamaIndex, or equivalent; multi-agent frameworks (CrewAI, AutoGen, or similar)
Vector databases — Pinecone, Weaviate, Chroma, pgvector, or equivalent
Containerisation and CI/CD — Docker, basic Kubernetes, GitHub Actions
5-14 years enterprise technology experience; minimum 2 years in production AI delivery

Anthropic / Claude Ecosystem — Strongly Preferred

Given the practice's primary AI platform orientation, depth in the Anthropic/Claude ecosystem is a material differentiator. Candidates with hands-on production experience across multiple Claude capabilities will be prioritised.

Claude API — tool use, computer use, vision, and document processing in production applications
Claude Code — agentic coding workflows, CLI integration, MCP server configuration, and multi-agent software development pipelines
Claude claude.ai and Projects — enterprise deployment patterns, system prompt design, memory and context management
Anthropic prompt engineering — chain-of-thought elicitation, XML-structured outputs, multi-turn conversation design, and retrieval-augmented prompting
Claude model family knowledge — Opus, Sonnet, Haiku trade-offs for latency, cost, and capability in production architectures
MCP (Model Context Protocol) — server implementation, tool registration, and integration with enterprise data sources (Google Drive, Gmail, Slack, CRMs)
Anthropic API batch processing, streaming, and rate limit management for enterprise-scale deployments
AI safety and responsible AI design aligned with Anthropic's principles

Broader AI Tooling — Preferred

Local LLM deployment — Ollama, Qwen, Mistral, Llama on Apple Silicon or equivalent edge hardware for air-gapped or data-sovereign deployments
GitHub Copilot, Cursor, or equivalent AI-assisted development environments — production use in SDLC automation contexts
Open-source agent frameworks — LangGraph, AutoGen, CrewAI, or equivalent for multi-agent orchestration
SDLC and DevTest automation — AI-assisted test generation, code review pipelines, and CI/CD integration
Security and compliance design — data residency, air-gapped deployment patterns, PDPA and MAS regulatory considerations for Singapore deployments
Front-end familiarity — React or equivalent for building lightweight internal tools and executive dashboards

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required:

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, Analytical Thinking, C++ Programming Language, Coaching and Feedback, Communication, Complex Data Analysis, Creativity, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Embracing Change, Emotional Regulation, Empathy, GPU Programming, Inclusion, Intellectual Curiosity, Java (Programming Language), Learning Agility {+ 30 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

Yes

Government Clearance Required?

Job Posting End Date

How we rate this

AI Solution Architect at PwC rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

AI Solution Architect is an open job at PwC.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Singapore.
The job was posted on July 1, 2026.
Seniority: senior.
Applications are handled by PwC. Apply on PwC

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGLLM IntegrationAI agentsAI SafetyAPI DevelopmentData EngineeringMulti Agent Frameworks

Also common in solutions architect jobs at this level

Generative AI SQL Machine learning Spark MLOps Snowflake

Pay

Typical solutions architect job: $169k

This posting doesn't list pay. Use the typical solutions architect figure when pay comes up. See solutions architect jobs

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
How have you integrated a large language model into a production application?
How do you decide when an AI agent can act on its own versus asking for approval first?
How do you think about the risk of an AI system in this kind of role failing silently?

Adapt your resume

List these exact terms on your resume: Prompt engineering, RAG, LLM Integration, AI agents, and AI Safety. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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