21 hours ago
Bengaluru, IndiaMid Level
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 for data flow and system interoperability.
- Develop, test, maintain, review, and troubleshoot application code across development and deployment environments.
- Support CI/CD pipelines, version control, release activities, testing, monitoring, and production operations.
- Build and deploy machine learning, generative AI, LLM-powered applications, RAG architectures, and agentic or multi-agent systems.
- Develop AI evaluation frameworks and apply observability tools to assess model, RAG, agent, and tool-call performance.
- Contribute to solution architecture, technical documentation, development standards, scalability, and performance optimization.
- Collaborate with client teams to gather requirements, interpret feedback, and adapt technical solutions.
- Mentor junior team members through code reviews, technical guidance, and practical problem-solving.
Requirements
- Bachelor's degree required.
- At least 4 years of experience required.
- Oral and written proficiency in English required.
- Preferred fields of study include Artificial Intelligence, Business Analytics, Computer and Data Engineering, Computer Science, Human Computer Interaction, Industrial Engineering, Information Systems or Technology, Machine Learning, Management Information Systems, and Software Engineering.
- Strong hands-on experience with Machine Learning, Deep Learning, Generative AI, and Agentic AI, including proven production implementations.
- Experience building, training, fine-tuning, evaluating, and deploying models using PyTorch, TensorFlow, Scikit-learn, and Hugging Face.
- Experience developing LLM-powered applications using Claude, GPT, open-source models, and enterprise AI platforms.
- Experience with RAG architectures, embeddings, vector databases, semantic search, and context engineering.
- Experience building AI agents and multi-agent systems using LangGraph, LangChain, CrewAI, AutoGen, or equivalent frameworks.
- Experience with agent orchestration, planning, reasoning, tool calling, memory, state management, human-in-the-loop workflows, MCP, and A2A protocols.
- Experience designing AI agent harnesses and evaluation frameworks covering LLM-as-a-Judge, RAG quality, hallucination detection, agent task success, and tool-call accuracy.
- Experience with AI observability and evaluation tools such as LangSmith, Langfuse, Ragas, DeepEval, or Arize Phoenix.
- Mandatory full-stack development experience with Python, Java or TypeScript, REST APIs, microservices, and React or Angular.
- Mandatory cloud engineering experience with AWS, Azure, or GCP, including Docker, Kubernetes, serverless architectures, and cloud-native deployments.
- Strong experience with MLOps, DevOps, CI/CD, Terraform, automated testing, security, and production monitoring for AI applications.
- End-to-end production delivery experience covering architecture, development, deployment, scalability, performance optimization, and operational support.
- Client-facing software engineering experience on integration engagements and the ability to translate technical concepts into business-focused recommendations.
- Bonus qualifications include Anthropic certifications or training, Claude Code, Claude Agent SDK, custom agent harnesses, agent skills, subagents, hooks, and AI-powered developer tooling.
Tech Stack
AngularAWSAzureDockerGoogle Cloud PlatformJavaJavaScriptKubernetesPythonPyTorchReactscikit-learnTensorFlowTerraformTypeScript
Categories
About PwC
PwC is a global network of professional services firms providing assurance, tax, and advisory work for businesses and public-sector clients. It sells project-based and managed consulting, audit, and deals services, and implements and integrates business applications. Formed in 1998 by the merger of Price Waterhouse and Coopers & Lybrand, it is headquartered in London and is one of the Big Four accounting firms.