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AI Engineer / Data Scientist (Agentic AI) | Manager/Senior Manager
PWC Australia —Sydney NSW
- Azure
- Research
- Master's degree
- Parental leave
4d

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AI Engineer / Data Scientist (Agentic AI) | Manager/Senior Manager
PWC Australia —Sydney NSW
Health and lifestyle perks like a wellness credit and discounted memberships. As an AI Engineer / Data Scientist on our team, you will design, build and…
4d

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AI Engineer / Data Scientist (Agentic AI) | Manager/Senior Manager

PWC Australia -
Sydney NSW

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Job Details

4 days ago

Benefits

Parental leave

Qualifications

Azure
Law
Full-stack development
Git
Research
Master's degree
Databases
Microservices
Docker
PostgreSQL
RabbitMQ
Natural language processing
Data pipeline
Agile
AI
Communication skills
SDLC

Full Job Description

The AI team is comprised of highly experienced designers, developers, data scientists and analysts who are responsible for delivering digital products and AI solutions to PwC’s business in Australia.

The Opportunity

The AI team is comprised oAI Engineer / Data Scientist (Agentic AI) f highly experienced designers, developers, data scientists and analysts who are responsible for delivering digital products and AI solutions to PwC’s business across multiple lines of service in Australia.

We partner with subject matter experts across the business to advise on, design and build agentic AI systems and LLM-powered products that transform the way we deliver assurance, advisory, tax and legal services to our clients.

About The Role

As an AI Engineer / Data Scientist on our team, you will design, build and evaluate production agentic AI systems, LLM applications that reason, call tools, retrieve knowledge and complete multi-step tasks on behalf of our practitioners and clients. You will own problems end to end: from framing the approach and prototyping, to shipping reliable, observable agents at scale in the Azure cloud.

We are a data science team at heart, so we care deeply about rigour: measuring agent quality, running evaluations, and using the scientific method to know whether something actually works, not just whether it demos well.

On a day-to-day basis you will be:

Building agentic solutions: agents that plan and execute multi-step tasks over long horizons, with context compaction and tool-call repair so they stay reliable and on-budget.

Designing and expanding agent tool ecosystems: file/document operations, sandboxed code and bash execution, web search, and enterprise integrations (e.g. MS Graph) — with well-typed, testable schemas.

Orchestrating multi-agent / sub-agent systems that spawn parallel sub-tasks, coordinate, and report results back to a lead agent.

Building stateful LLM workflows (e.g. LangGraph) for domain pipelines such as research, summarisation and report generation.

Engineering RAG and retrieval pipelines: chunking, embeddings, vector search (pgvector / Azure AI Search), hybrid and re-ranked retrieval, and grounding LLM outputs in trusted sources.

Producing structured, reliable LLM outputs (function calling / Pydantic) and designing robust prompts and agent skills.

Building evaluation harnesses and offline batch evals (including deep-research style runs) to measure accuracy, faithfulness, cost and latency — and using those signals to iterate.

Instrumenting agents with observability and tracing (e.g. Langfuse, OpenTelemetry) and tracking token usage and cost in production.

Routing across multiple models and providers via an enterprise gateway (e.g. LiteLLM) and tuning model selection for quality, latency and cost.

Producing clean, maintainable, efficient code deployed at scale in the Azure cloud; scaffolding new projects, pairing with engineers, and reviewing pull requests.

Contributing to team stand-ups and the broader software development lifecycle, and participating in firmwide data science, ML and AI forums.

Coaching and mentoring junior data scientists and engineers.

Key capabilities and behaviours Applicants must be able to demonstrate the following key capabilities. We do not expect every candidate to tick every box, strong fundamentals and a track record of shipping LLM-powered products matter most.

Strong Python development experience, with hands-on use of modern LLM frameworks and SDKs (e.g. OpenAI / Anthropic SDKs, LiteLLM, LangGraph).

Deep, practical knowledge of prompt engineering, LLM workflows and agentic patterns, tool/function calling, multi-step agents, and structured outputs.

Experience building and optimising RAG pipelines, including evaluation, with industry-standard tooling.

Working knowledge of vector databases such as pgVector and Azure AI Search, plus embeddings and hybrid/semantic search.

Strong experience with SQL databases such as PostgreSQL (or equivalents).

A scientific, evaluation-first mindset: selecting appropriate methods, applying algorithms at scale, and using the scientific method to derive robust, defensible conclusions about model and agent behaviour.

Strong critical thinking, analytical rigour and outstanding attention to detail.

Proper source code management and confident use of Git.

Good written and verbal communication, and the ability to work effectively with remote teams.

A proactive, problem-solving approach and the ability to solve complex problems as part of a team.

Highly regarded (nice to have):

Experience with LLM observability and cost/quality tracing (e.g. Langfuse, OpenTelemetry).

Experience routing across multiple models/providers (e.g. via LiteLLM or an enterprise gateway) and reasoning about model selection trade-offs.

Experience designing multi-agent / sub-agent systems and agent tool ecosystems (web search, file/document tools, enterprise integrations such as MS Graph).

Experience with computer-use / browser-automation agents (e.g. Playwright).

Knowledge of classical ML (regression/boosting) and deep learning (CNN/RNN), preferably in NLP or CV.

A research background in ML/LLM model development, and the ability to identify emerging techniques and apply them to practical situations.

Experience with microservices, containerisation (Docker), and building/operating data pipelines at scale.

Experience with message-queueing solutions (e.g. RabbitMQ, Kafka).

Experience developing on cloud environments, particularly Azure (Azure OpenAI, AI Search, Blob, Key Vault, App Insights).

Knowledge of agile software development lifecycles (SDLC) and experience on agile projects.

TypeScript / full-stack experience is a strong bonus: much of our agent tooling and UI is built in TypeScript (Vercel AI SDK, NestJS, Next.js / React), and being able to work across the Python and TypeScript stack is highly valued.

About PwC

At PwC, we are a human-led, tech-powered community of solvers. We approach problems with curiosity, collaboration and willingness to challenge the status quo to develop innovative solutions in partnership with Australian businesses and not-for-profits. Together, we strive to make a positive impact and drive meaningful change.

That’s where our people come in. Whether you’re just beginning your career or have plenty of experience under your belt, we believe your unique perspective can help us to deliver valued insights that make a real impact. Here, you’ll be surrounded by peers who have your back and leaders who support you, in an environment that encourages continuous learning and growth.

Your benefits

Flexible working arrangements for how, where and when you work, ensuring you thrive while delivering top results for your team and clients

More opportunities to connect with loved ones, with the ability to work up to four weeks from anywhere in Australia and select international locations

Health and lifestyle perks like a wellness credit and discounted memberships

Gender inclusive 26 weeks paid parental leave

World-class development opportunities to accelerate your career

Strong mentors, meaningful work and plenty of networking opportunities

Dress for your day so you can feel confident and comfortable for whatever your day has in store for you

Our commitment to diversity and inclusion

We empower our people to use their creativity, authenticity and human differences to be champions of change and challenge our thinking. At PwC, we understand that diverse perspectives are necessary for solving complex problems. We believe that for diversity to truly flourish, it must be nurtured in an inclusive environment. That's why we are committed to fostering a workplace where everyone feels valued to thrive.

PwC is committed to making our recruitment processes inclusive, so if you need reasonable adjustments or would like to note which pronouns you use at any point in the application or interview process, please let us know.

No Agencies Please: We kindly request that recruitment agencies do not submit CVs in response to this advertisement. We are only accepting applications direct from individuals.

Apply Now

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AI Engineer / Data Scientist (Agentic AI) | Manager/Senior Manager

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