Job Description: Senior Full-Stack AI Engineer Role Overview: We are seeking a highly skilled Senior Full-Stack AI Engineer to join our innovation team.

This role sits at the intersection of robust software engineering and cutting-edge Artificial Intelligence.

You will be responsible for designing and implementing scalable web applications, architecting sophisticated AI workflows, and deploying intelligent agents capable of complex reasoning.

The ideal candidate is a polyglot engineer who is equally comfortable building high performance React frontends, resilient Python backends, and integrating Java-based enterprise services, all while pushing the boundaries of Agentic AI and Large Language Model (LLM) orchestration.

Key Responsibilities Full-Stack Development: Design and develop end-to-end web applications using React.js for interactive user interfaces and Python for high-performance backend logic and AI orchestration. AI Orchestration & Agentic Workflows: Architect and implement advanced Multi Agent Systems (MAS) and Agentic AI workflows that can perform autonomous reasoning, tool use, and multi-step task execution.

Generative AI Implementation: Build and optimize RAG (Retrieval-Augmented Generation) pipelines to connect LLMs/SLMs to private data sources, ensuring high accuracy and reduced hallucination. AI Ecosystem Integration: Implement and manage the Model Context Protocol (MCP) to standardize how AI models interact with external tools and data sources.

Backend & Enterprise Integration: Develop scalable microservices using Java to ensure seamless integration between AI modules and core enterprise business logic.

Cloud & Data Engineering: Deploy and manage scalable AI workloads and data pipelines using AWS and Databricks, ensuring optimized performance for model training and inference.

System Architecture: Design scalable, secure,



and fault-tolerant architectures capable of handling real-time AI interactions and large-scale data processing.

Technical Qualifications 1.

Core Engineering: Frontend: Expert-level proficiency in React.js, Type

Script, and modern state management (Redux, Zustand, or React Query).

Backend (AI/Logic): Advanced proficiency in Python (FastAPI, Flask, or Django) for AI service orchestration.

Backend (Enterprise): Strong experience in Java (Spring Boot) for building robust, scalable microservices. 2.

Artificial Intelligence: LLM/SLM Mastery: Hands-on experience working with Large Language Models (GPT-4, Claude, Llama) and Small Language Models (SLMs) for specialized tasks.

Agentic Frameworks: Deep understanding of agentic design patterns and experience with frameworks such as Lang

Chain, Lang

Graph, CrewAI, or Auto

Gen. RAG Expertise: Proven ability to build production-grade RAG systems using vector databases (e.g., Pinecone, Milvus, Weaviate, or FAISS).

Emerging Standards: Familiarity with or experience implementing the Model Context Protocol (MCP) to extend model capabilities. 3.

Cloud & Data Stack: AWS: Proficiency in AWS services (EC2, Lambda, S3, Sage

Maker, Bedrock, ECS/EKS).

Databricks: Experience with Databricks for large-scale data processing, Delta Lake, and managing MLflow for model lifecycle management.

Preferred Skills & Qualifications Experience with Vector Databases and efficient embedding strategies. Understanding of containerization (Docker, Kubernetes) and CI/CD pipelines. Knowledge of distributed computing and handling asynchronous task queues (Celery, RabbitMQ). Robust mathematical foundation in machine learning and neural network architectures. Ability to translate complex business requirements into scalable technical architectures.

Soft Skills Problem Solver: Ability to tackle "unsolved" problems inherent in non-deterministic AI outputs.

Architectural Thinking: Ability to see the big picture of how data, models, and UI interact.

Agility: Comfortable working in a fast-paced, research-driven environment.

📌 Full Satck AI Engineer - Deloitte (India)
🏢 TRIGENT SOFTWARE PRIVATE
📍 India