AI & Full Stack Software Engineer

Analyst-KDNI

We’re hiring future-ready engineers who want to be at the intersection of AI innovation, software engineering, and enterprise architecture. You will be a core contributor to solutions that use AI agents, microservices, and full stack engineering to build real-world applications in domains such as Audit, Tax, ESG, and Legal transformation.
You’ll be part of the Agentic AI Engineering Pod within KPMG Delivery Network (KDN) AI Foundry, working across modern AI platforms, intelligent orchestration frameworks, and cloud-native development environments.

Agentic AI Development
• Participate in building and scaling agent-based applications using frameworks like CrewAI, Autogen, Semantic Kernel, LangGraph, etc.
• Work with APIs from OpenAI, Azure AI, Google Gemini, Meta AI and open-source LLMs (LLaMA, Falcon, Mistral).
• Contribute to retrieval-augmented generation (RAG), memory-augmented agents, and multi-agent systems aligned with business workflows.

Full Stack and Backend Engineering
• Develop UI components and interfaces using React.js, Next.js, HTML5, CSS3, TypeScript.
• Build backend services with Python (FastAPI/Flask), Node.js, or Java/Spring Boot.
• Enable real-time interactions using APIs, webhooks, and secure integrations (OAuth2, JWT).

Database and Storage Integration
• Work on structured and semi-structured data using PostgreSQL, MongoDB, MySQL, and Snowflake.
• Build vectorized and semantic search experiences with Pinecone, FAISS, Weaviate, or Milvus.
• Leverage knowledge graphs using Neo4j or Amazon Neptune for complex relationship mapping.

Architecture & Microservices
• Design and containerize services with Docker and orchestrate deployments using Kubernetes.
• Collaborate on building loosely coupled microservices hosted on Azure, GCP, or AWS.
• Understand MLOps, observability, and model versioning frameworks (MLflow, ArgoCD, Prometheus).

Required
• Hands-on experience in building projects using web technologies and backend services
• Sound understanding of object-oriented design, clean code practices, and SDLC
• Academic or personal projects involving AI/ML/NLP/LLMs
• Knowledge of authentication, secure coding, and API documentation

Good to Have
• GitHub portfolio showcasing coding style or ML/AI projects
• Experience with LangChain, LangGraph, or any agentic/LLM toolkits
• Competitions (Hackathons, Kaggle, CodeChef, etc.) or tech communities

Candidate Profile
• Degree: B.Tech/ Dual Degree (Computer Science, Software Engineering, AI/ML, or similar)
• Graduation Year: 2026

Experience Level

Entry Level