Risk Services - AI Factory: Forward Deployed Engineer (Senior Associate / Manager / Senior Manager)

PwC is hiring a Risk Services - AI Factory: Forward Deployed Engineer (Senior Associate / Manager / Senior Manager) for a remote role open to applicants in Singapore. Level rates it ; you can apply on PwC.

Level's read on this job

Level rates this forward deployed engineer role Builds AI ●●●●: the job is building AI systems.
This is listed as a remote role.
The posting mentions visa sponsorship.
The posting mentions LLMs, Python and Open Source Frameworks among its tools and skills.
PwC has 3,700+ other open roles on Level.

AI in this role

Forward Deployed Engineer in PwC's AI Factory building, deploying, and maintaining Generative AI solutions and data pipelines for clients.

LLMsPythonOpen Source Frameworks

prompt-engineeringragml-opsgenerative-aimachine-learningdata-pipelinessoftware-engineeringstakeholder-management

Line of Service

Assurance

Industry/Sector

Not Applicable

Specialism

Analytics

Management Level

Senior Associate

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.

About the AI Factory

The AI Factory drives AI innovation across the PwC network, fostering collaboration across PwC territories to deliver faster, high-impact AI solutions that enhance client service delivery.

About the Role

As a Forward Deployed Engineer, you'll work at the intersection of cutting-edge AI development and real-world client delivery. Embedded directly with teams across our lines of service, you'll build, deploy, and maintain Generative AI solutions on the ground, translating complex business challenges into working products and actionable insights. This is a hands-on, client-facing role for engineers who want to see their work create impact in the field.

What You'll Do

Build and deploy AI solutions: Develop, deploy, and maintain Generative AI models and data analysis pipelines to collect, explore, and extract insights from client and engagement data.
Collaborate with stakeholders: Communicate and collaborate effectively with engagement teams and key stakeholders, supporting risk management and governance processes throughout delivery.
Own end-to-end delivery: Manage projects from start to finish, clarifying requirements and designing analytical approaches aligned to business objectives.

How the Role Scales

Senior Associate: Operates as a strong individual contributor, building and deploying solutions while developing client-facing skills.
Manager: Leads workstreams, owns solution delivery, and guides junior engineers while managing stakeholder relationships.
Senior Manager: Shapes the technical direction of engagements, leads teams across multiple workstreams, and drives AI strategy in partnership with senior client and PwC leadership.

What You'll Bring

A degree in a quantitative field (Data Science, Computer Science, Applied Statistics, Mathematics, or similar) with 3+ years of relevant experience.
Hands-on experience with LLMs, open-source frameworks, big data technologies, machine learning, and numerical programming tools.
Strong proficiency in Python.

Nice to Have

Experience with cloud platforms (Azure, AWS, or GCP).
Familiarity with RAG pipelines, vector databases, and prompt engineering.
Exposure to MLOps and productionizing machine learning systems.
Prior consulting or client-facing experience.

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, 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, Machine Learning {+ 25 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

Risk Services - AI Factory: Forward Deployed Engineer (Senior Associate / Manager / Senior Manager) at PwC rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● 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

Risk Services - AI Factory: Forward Deployed Engineer (Senior Associate / Manager / Senior Manager) is an open job at PwC.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Singapore and is marked remote.
The job was posted on June 24, 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 engineeringRAGML OpsGenerative AIMachine learningData PipelinesSoftware EngineeringStakeholder Management

Also common in forward deployed engineer jobs at this level

AI agents TypeScript React Fine-tuning JavaScript LangChain

Pay

Typical forward deployed engineer job: $180k

This posting doesn't list pay. Use the typical forward deployed engineer figure when pay comes up. See forward deployed engineer 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 do you monitor a model once it's live, and how do you know it needs retraining?
Tell me about a project where generative ai was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Prompt engineering, RAG, ML Ops, Generative AI, and Machine learning. 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.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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