: 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, TypeScript, 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 LangChain, LangGraph, CrewAI, or AutoGen.

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.

- Cloud &
- Data Stack: AWS: Proficiency in AWS services (EC2, Lambda, S3, SageMaker, 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).
- Strong 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 quick-paced, research-driven environment.

📌 Full Satck AI Engineer - Deloitte (India)
🏢 Trigent Software
📍 India