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PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

AI Engineer – Senior Associate

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • At least a bachelor's degree.
  • At least 4 years of experience.
  • Oral and written proficiency in English is required.

Responsibilities

  • Design and develop AI-enabled software components, services, and integrations across enterprise platforms.
  • Translate business requirements into scalable technical solutions using software engineering methods and architecture patterns.
  • Build and refine APIs, microservices, and application interfaces to support data flow and system interoperability.
  • Apply Python, Java, JavaScript, or similar programming languages to create, test, and maintain application code.
  • Review code, troubleshoot defects, and resolve issues across development and deployment environments.
  • Support CI/CD pipelines, version control, and release activities to improve delivery speed and code reliability.
  • Collaborate with client teams to gather requirements, interpret feedback, and adapt technical solutions to changing needs.
  • Evaluate AI fluency, AI-human collaboration, and digital tooling to improve automation and application performance.
  • Contribute to solution architecture, technical documentation, and development standards for enterprise software delivery.
  • Mentor junior team members through code reviews, technical guidance, and practical problem-solving.

Desired Qualifications

  • A preferred field of study is Artificial Intelligence, Business Analytics, Computer and Data Engineering, Computer Science, Human Computer Interaction, Industrial Engineering, Information Systems/Technology, Machine Learning, Management Information Systems, or Software Engineering.
  • Demonstrate client-facing software engineering experience on integration engagements.
  • Apply Python, Java, or JavaScript in AI solution development.
  • Develop APIs, microservices, or enterprise application architecture.
  • Use CI/CD, testing, and code review practices in delivery work.
  • Mentor junior team members while navigating ambiguity.
  • Translate technical concepts into business-focused recommendations.
  • Have hands-on experience in Machine Learning, Deep Learning, Generative AI, and Agentic AI, with proven production implementations.
  • Have experience building, training, fine-tuning, evaluating, and deploying ML models using PyTorch, TensorFlow, Scikit-learn, and Hugging Face.
  • Have hands-on experience developing LLM-powered applications using Claude, GPT, open-source models, and enterprise AI platforms.
  • Have experience implementing RAG architectures, embeddings, vector databases, semantic search, and context engineering.
  • Have experience designing and building AI agents and multi-agent systems using LangGraph, LangChain, CrewAI, AutoGen, or equivalent frameworks.
  • Have experience implementing agent orchestration, planning, reasoning, tool calling, memory, state management, and human-in-the-loop workflows.
  • Have hands-on experience with MCP, A2A protocols, API integrations, and enterprise tool connectivity.
  • Have a strong understanding of AI agent harness architecture, including execution loops, context management, tool permissions, guardrails, and error recovery.
  • Have experience building AI evaluation frameworks covering LLM-as-a-Judge, RAG quality, hallucination detection, agent task success, and tool-call accuracy.
  • Have hands-on experience with AI observability and evaluation tools such as LangSmith, Langfuse, Ragas, DeepEval, or Arize Phoenix.
  • Have mandatory full-stack development experience with Python, Java/TypeScript, REST APIs, microservices, and frontend frameworks such as React or Angular.
  • Have mandatory cloud engineering experience with AWS, Azure, or GCP, including Docker, Kubernetes, serverless architectures, and cloud-native deployments.
  • Have strong experience in MLOps, DevOps, CI/CD, Terraform, automated testing, security, and production monitoring for AI applications.
  • Have demonstrated real-world, end-to-end production delivery experience, including architecture, development, deployment, scalability, performance optimization, and operational support.
  • Anthropic certifications or training, Claude Code, Claude Agent SDK, custom agent harnesses, agent skills, subagents, hooks, and AI-powered developer tooling are a bonus.

About the Company

PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

PwC provides assurance (audit), tax, legal services, consulting and deals advisory to organisations worldwide. It uses multidisciplinary teams across accounting, advisory, technology and industry, delivered through a global network of locally established firms that collaborate with technology partners to offer AI, cloud, managed services and digital trust. PwC differentiates itself with an integrated, global-local service model and technology-enabled offerings that address complex client needs across risk, transformation, reporting and sustainability. Its goal is to help clients improve governance, efficiency and value by supporting reporting accuracy, business transformation, risk management and sustainable practices.

Company size
10,001+
Company stage
Early VC
Total funding
$3.3M
Headquarters
London, United Kingdom
Founded
1989

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