Associate​/Senior Associate - Cloud, Data and AI; CD&AI - Cloud & AI Engineer

Line of Service

Advisory

Not Applicable

Emerging Technologies

Senior Associate

PwC’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.

• 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 more 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

• 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 No
  
  SQL databases (e.g., Postgre
  
  SQL, Mongo
  
  DB)
• Working knowledge of CI/CD pipelines and automated testing
• Experience with cloud deployments on Azure (preferred) or AWS/GCP, including containerization

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

• 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, Git Hub Copilot, Devin, Claude Code, or similar)

• 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

• Proficiency in Go or Rust in addition to Python
• Experience with MLOps practices (model versioning, monitoring, retraining pipelines)

• Technical degree in Computer Science, Data Science, Engineering, Mathematics, Physics, or…