Associate / Senior Associate - Cloud, Data and AI (CD&AI) - Cloud & AI Engineer

Description

& SummaryPwC’s Cloud, Data & AI team builds AI systems that go to production and stay there. We work directly with clients to design, develop, and deploy Generative AI applications in cloud environments, solving real business problems at scale.
This is a hands-on engineering role. You will own solutions from architecture through deployment. You will also sit across from clients, understand their challenges, and translate them into working systems. We invest heavily in AI-augmented development tooling so you will have access to state-of-the-art models, infrastructure, and autonomous ai coding systems. We need engineers who understand how to orchestrate this, who can think architecturally, make sharp technology choices, understand how to manage the risks, design systems and direct autonomous workflows, and ensure what comes out is production-grade.

What You Will Do

• Architect solutions: Define system design, select technologies, and make decisions that shape entire projects
• Orchestrate autonomous coding workflows: Direct AI coding agents to generate, test, and refine code while you maintain quality, coherence, and architectural integrity
• Build end-to-end AI applications: Deliver Generative AI solutions from concept through production deployment
• Work directly with clients: Understand business problems, propose technical approaches, and ship working systems
• Deploy and operate in the cloud: Ship on Azure (preferred) as well as GCP / AWS, manage infrastructure, and ensure reliability at scale
• Design data architecture: Build and maintain data pipelines, database integrations, and vector stores that power AI applications
• Maintain engineering discipline: Autonomous code generation demands rigor, not less: testing, review, CI/CD, and monitoring are non-negotiable
• Push the craft forward : Contribute to internal accelerators, reusable frameworks, and methodologies that define how AI-augmented engineering works at PwC

What You Bring

Engineering Fundamentals

• Strong proficiency in Python and familiarity with all SOTA AI/ML frameworks is a must
• Track record of building and shipping production-level applications
• Experience with REST APIs and backend development
• Solid Git workflows (pull requests, branching strategies, code reviews)
• Experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB)
• Working knowledge of CI/CD pipelines and automated testing
• Experience with cloud deployments on Azure (preferred) or AWS/GCP, including containerization

AI & Generative AI

• Hands-on experience building AI/ML applications — deployed systems, not just notebooks
• Experience integrating large language model APIs (e.g., Azure OpenAI or comparable)

Working understanding of:

• ​RAG architectures
• Embeddings and vector databases
• Prompt engineering and optimization
• Model evaluation and monitoring
• Experience with or strong interest in AI-powered development tools and agentic coding workflows (e.g., Cursor, GitHub Copilot, Devin, Claude Code, or similar)

Mindset & Working Style

• You think in systems, not tasks — you see the full architecture before writing the first line
• You treat AI agents as tools to be directed, not magic to be hoped at — you know how to specify, constrain, review, and iterate
• You take ownership of outcomes and move fast without sacrificing quality
• You communicate clearly with both technical and non-technical stakeholders
• You stay current with a field that moves weekly and are genuinely excited about the transformation underway in software engineering

What Sets You Apart

• Proficiency in Go or Rust in addition to Python
• Experience with MLOps practices (model versioning, monitoring, retraining pipelines)
• Demonstrated ability to manage and orchestrate multiple AI coding agents in parallel
• Experience working in agile delivery teams in a consulting or client-facing context
• Contributions to open-source projects or a visible portfolio of AI-related work
• Experience with multi-agent architectures or autonomous AI systems

Qualifications

• Technical degree in Computer Science, Data Science, Engineering, Mathematics, Physics, or equivalent practical experience
• Evidence of building AI applications beyond coursework — production systems, significant personal projects, or meaningful open-source contributions

What We Offer

• Unlimited AI access: No token limits, no budget gates. Full access to leading AI models, coding agents, and cloud infrastructure to explore and build without constraints
• The future of engineering, now: A team that is actively defining how software is built with autonomous AI workflows, not waiting for others to figure it out
• Real problems at scale: Client work across industries where your solutions have measurable business impact
• Growth through exposure: Work alongside experienced engineers, data scientists, and consultants on diverse engagements
• Technical community: An internal engineering culture that values building, sharing knowledge, and raising the bar collectively
• Career development: Clear progression paths with investment in your continuous learning

Education

Degrees/Field of Study required:Degrees/Field of Study preferred:

Certifications

Required Skills

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Algorithm Development, Alteryx (Automation Platform), Analytic Research, Big Data, Business Data Analytics, Communication, Complex Data Analysis, Conducting Research, Customer Analysis, Customer Needs Analysis, Dashboard Creation, Data Analysis, Data Analysis Software, Data Collection, Data-Driven Insights, Data Integration, Data Integrity, Data Mining, Data Modeling, Data Pipeline, Data Preprocessing, Data Quality {+ 33 more}

Desired Languages

Travel Requirements

Up to 20%

Available for Work Visa Sponsorship?

No

Government Clearance Required?

No

Job Posting End Date