Fullstack Engineer(angular/react+Python+Gen Ai)

Role & responsibilities

Role Overview

• Develop and maintain scalable web applications and APIs using

  Python

  (FastAPI, Flask, Django) and

  modern frontend frameworks

  (

  React.js, Angular.js

  ). 
• Build intuitive, responsive UIs using

  JavaScript/TypeScript

  ,

  CSS3

  ,

  Bootstrap

  , and

  Material UI

  for AI-powered products. 
• Collaborate closely with product teams to deliver

  GenAI/RAG-based solutions

  . 
• Design backend services for:  
• Data pipelines (

  Azure Data Factory

  ,

  Data Lake

  ,

  Delta Lake

  ) 
• Model inference 
• Embedding and metadata storage (SQL, NoSQL,

  Vector DBs

  ) 
• Optimize application performance for

  AI inference

  and

  data-intensive workloads

  . 
• Integrate third-party APIs, model-hosting platforms (

  OpenAI

  ,

  Azure ML

  ,

  AWS SageMaker

  ), and

  vector databases

  . 
• Implement robust CI/CD pipelines using

  Azure DevOps

  ,

  GitHub Actions

  , or

  Jenkins

  . 
• Participate in architectural reviews and contribute to design best practices across the engineering organization. 

Required Skills & Experience

• 46 years

  of professional full-stack engineering experience. 
• Bachelor's degree in Computer Science, Engineering, or related technical field (BE/BTech/MCA) 
• Strong Python development skills, particularly with

  FastAPI

  ,

  Flask

  , or

  Django

  . 
• Experience with data processing using

  Pandas

  . 
• Proficient in

  JavaScript/TypeScript

  with at least one modern frontend framework (

  React

  ,

  Angular

  ). 
• Solid understanding of

  RESTful

  and

  GraphQL

  API design. 
• Experience with at least one cloud platform:  

• Azure

  : Functions, App Service, AI Search, Service Bus, AI Foundry 

• AWS

  : Lambda, S3, SageMaker, EC2 
• Hands-on experience building

  GenAI

  applications using

  RAG

  and

  agent frameworks

  . 
• Database proficiency with:  

• Relational

  databases: PostgreSQL, SQL Server 

• NoSQL

  databases: MongoDB, DynamoDB 

• Vector stores

  for embedding retrieval 
• Familiarity with

  LLM orchestration tools

  : LangChain, AutoGen, LangGraph, Crew AI, A2A, MCP 
• Understanding of

  Responsible AI

  practices and working knowledge of

  LLM providers

  (OpenAI, Anthropic, Google PaLM, AWS Bedrock) 

• Good to Have Skills

• DevOps & Infrastructure

  : Terraform, Kubernetes, Docker, Jenkins 

• MLOps capabilities

  : model versioning, inference monitoring, automated retraining 
• Security experience with

  OpenID Connect

  ,

  OAuth2

  ,

  JWT

• Deep experience with data platforms:

  Databricks

  ,

  Microsoft Fabric

• Prior experience in

  AI/ML R&D

  or working within

  cross-functional product teams

Soft Skills & Team Expectations

• Effective communication and documentation skills; ability to clearly articulate technical concepts to both technical and non-technical audiences. 
• Demonstrated ability to work independently as well as collaboratively in a fast-paced environment. 
• A builder's mindset with a powerful desire to

  innovate, automate, and scale

  . 
• Comfortable in an agile, iterative development environment. 
• Willingness to mentor junior engineers and contribute to team knowledge growth. 
• Proactive in identifying tech stack improvements, security enhancements, and performance bottlenecks. 

Preferred Certifications(at least two are preferred)

• Cloud Certifications

  (Azure, AWS, GCP) – e.g.,

  Azure DevOps Engineer

  ,

  AWS Certified ML Specialist

  ,

  GCP Professional ML Engineer

• Docker/Kubernetes/Cloud Native certifications

  (CKAD, CKA, etc.) 

Why Join PwC CTIO?

• Work at the

  cutting edge of AI engineering

  , deploying real solutions at production scale. 
• Collaborate with

  visionary AI researchers

  , engineers, and product leaders to redefine what is possible. 
• Be part of a team that values both

  rapid experimentation

  and

  engineering excellence

  . 
• Gain exposure to

  LLMOps and GenAI infrastructure

  at an enterprise scale. 
• Join a culture that encourages

  continuous learning, bold thinking

  , and

  inclusive innovation

  . 

Shift:11am-8pm