Role Overview :
We are seeking a highly skilled Fullstack AI Engineer who can operate at the intersection of Artificial Intelligence, Machine Learning, Full-Stack Development, and DevOps.
This is a hands-on engineering role that requires expertise in designing, building, and deploying end-to-end AI-powered applications.
The ideal candidate has strong foundations in Python-based AI / ML, modern frontend frameworks, and cloud-native DevOps practices, with proven experience in delivering scalable, production-grade AI solutions.
Key Responsibilities :
AI / ML Engineering :
- Design and develop AI / ML models leveraging traditional ML as well as Generative AI (LLMs, Transformers, RAG, AI agents).
- Work with vector databases (Pinecone, Weaviate, FAISS, Milvus) for semantic search and retrieval-augmented generation.
- Implement prompt engineering techniques, fine-tuning pipelines, and evaluation frameworks for LLM-based solutions.
- Apply best practices in model deployment, monitoring, and optimization for latency, accuracy, and scalability.
Backend Engineering :
Develop and scale APIs using FastAPI, Django, or Flask.Architect and manage SQL / NoSQL databases (PostgreSQL, MongoDB, Redis, Cassandra).Implement async processing pipelines with Celery, Kafka, or RabbitMQ.Build secure, modular, and testable backend systems following clean architecture principles.Frontend Engineering :
Build modern, interactive UIs for AI-driven applications using React, Next.js, and TypeScript.Implement state management (Redux, Recoil, Zustand) for seamless user experiences.Integrate AI APIs into client-facing applications with high performance and reliability.Ensure responsive, accessible, and optimized frontend experiences for AI products.DevOps & Cloud Engineering :
Containerize applications with Docker and orchestrate with Kubernetes.Implement CI / CD pipelines for automated builds, testing, and deployments.Deploy AI applications on AWS, GCP, or Azure with scalability and fault-tolerance in mind.Monitor infrastructure performance, logs, and security using tools like Prometheus, Grafana, and ELK stack.Engineering Best Practices :
Drive code quality, modularization, and reusability across systems.Follow Git workflows (GitFlow, trunk-based) and enforce peer code reviews.Ensure application security through OWASP guidelines, API security, and cloud IAM best practices.Conduct unit testing, integration testing, and automated regression testing to ensure system : :Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or related field from a reputed institution.Strong academic foundation in algorithms, data structures, distributed systems, and applied mathematics.Professional Experience :
8+ years of experience in software engineering, with at least 4+ years in AI / ML-focused roles.Proven track record of designing, developing, and deploying AI-powered fullstack applications in production environments.Technical Competencies :
Expertise in Python (AI / ML + backend) and JavaScript / TypeScript (React / Next.js frontend).Solid understanding of traditional ML techniques, deep learning, and generative AI architectures.Experience with cloud-native deployments on AWS / GCP / Azure.Knowledge of CI / CD, containerization (Docker / Kubernetes), and MLOps workflows.Strong grasp of data modeling, API design, system architecture, and scalability patterns(ref : hirist.tech)
