Full Stack Agentic AI Engineer

Line of Service: Advisory Data, Analytics & AI

Specialization: Agentic AI, Full Stack Development

Management Level: Senior Associate

Experience: 68 Years

Location: Mumbai(Hybrid)

Job Description & Summary

A career within PwCs Data, Analytics & AI practice provides opportunities to help organisations unlock enterprise value using advanced analytics, cloud platforms, and intelligent AI systems. We combine cutting-edge Agentic AI, Full Stack Engineering, and Cloud technologies to build scalable, secure, and innovative solutions that drive real business outcomes.

As a Senior Associate Full Stack Agentic AI Engineer, you will design, build, and deploy endtoend AIpowered applications by integrating large language models (LLMs), agentic workflows, APIs, and modern front-end frameworks. You will work closely with data scientists, architects, and business stakeholders to deliver intelligent, productionready AI solutions at scale.

Why PwC

At PwC, youll be part of a global community of problem solvers who lead with trust and deliver distinctive value. Our purposeled culture, combined with technology and innovation, empowers you to make a meaningful impact while continuously growing your skills.

PwC is an equal opportunity employer. We promote an inclusive workplace with zero tolerance for discrimination or harassment, enabling everyone to bring their authentic selves to work and thrive professionally and personally.

About the Role

We are looking for a hands-on Full Stack Agentic AI Engineer with strong expertise in Python, cloud platforms, AI/ML, and front-end development. The ideal candidate is passionate about building intelligent, usercentric applications, implementing agent-based AI systems, and operating AI solutions responsibly at enterprise scale.

Key Responsibilities

• Design, develop, and maintain endtoend full stack AI applications using Python-based back-end frameworks (FastAPI / Flask / Django) and modern front-end frameworks (Angular / React, TypeScript, HTML5, CSS)
• Build and integrate Agentic AI systems, LLMs, and generative AI models into enterprise applications
• Develop and expose RESTful APIs to support AI-driven workflows and system integration
• Deploy and manage AI applications on cloud platforms (Azure / AWS), ensuring scalability, security, and performance
• Implement MLOps / LLMOps practices including model versioning, monitoring, evaluation, and retraining
• Manage data pipelines required for AI/ML workloads and inference
• Ensure adherence to data privacy, security, governance, and compliance standards
• Optimize system performance, reliability, and cost efficiency across AI and application layers
• Collaborate with data scientists, architects, product owners, and business stakeholders to translate requirements into technical solutions
• Stay current with advancements in Agentic AI, Generative AI, and full stack technologies, and contribute to innovation initiatives

Mandatory Skillsets

• 6+ years of experience in Full Stack Development and AI/ML solution delivery
• Strong expertise in Python and back-end frameworks (FastAPI, Flask, Django)
• Experience building and integrating LLMs, Generative AI, and Agentic AI workflows
• Solid knowledge of REST APIs, microservices architecture, and system integration
• Hands-on experience with cloud platforms (Azure/AWS), including AI and data services
• Experience with containerization and DevOps practices (Docker, CI/CD pipelines)
• Proficiency in front-end development using Angular or React, TypeScript, HTML5, and CSS
• Strong understanding of software engineering best practices, secure coding, testing, and performance optimization
• Excellent analytical, problem-solving, and communication skills

Preferred Skillsets

• Experience with MLOps / LLMOps frameworks and tools
• Exposure to Databricks, ML pipelines, or AI orchestration frameworks
• Knowledge of classical ML techniques, forecasting, or time-series analysis
• Familiarity with event-driven architectures and messaging systems
• Cloud or AI certifications (Azure AI Engineer, Azure Solutions Architect, AWS ML, etc.)

Qualifications

• Bachelors or Masters degree in Computer Science, Engineering, or a related field
• Ability to work effectively in agile, crossfunctional, global teams