Ai Ml Engineer

Trigyn Technologies Limited; New Delhi; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Trigyn Technologies Limited in Delhi is seeking an AI Developer to design, build and deploy AI-powered features within web applications. The role emphasizes Python/Node.js back-end services, REST APIs, and practical NLP solutions.

You will work with LLMs, NLP pipelines and production-grade AI components, collaborating across product and engineering teams to deliver scalable AI-enabled web apps.

Qualifications

• 3–6 years of hands-on AI/ML experience.
• Proficient in Python and Node.js for AI services and APIs.
• Experience with NLP tasks including modeling and evaluation.

Responsibilities

• Design AI-powered features and integrate into web apps.
• Develop AI services and REST APIs using FastAPI and Express.js.
• Prepare data, train, fine‑tune models and evaluate performance.
• Work with LLMs (OpenAI, Gemini, Claude) and productionize models.
• Utilize LangChain, LlamaIndex, Hugging Face tools.
• Implement AI security, privacy and responsible AI practices.
• Ensure scalable, reliable production deployments.
• Collaborate with product, engineering and UX teams.
• Create API specs and documentation (OpenAPI).
• Lead POC to production from requirement analysis to rollout.

Skills

AI/ML

NLP

Deep Learning

Generative AI

LLM Integration

API Development

REST APIs

Python

Node.js

FastAPI

Express.js

Tools

Python

Node.js

FastAPI

Express.js

OpenAI GPT

HuggingFace Transformers

spaCy

TensorFlow/Keras

PyTorch

LangChain

LlamaIndex

Pinecone

Job description

Job Description AI Developer

Role: AI Developer / AI Engineer

Experience: 3–6 Years (suggested)

Technical Focus: AI/ML, Deep Learning, NLP, Generative AI, Python (FastAPI), Node.js (Express.js), LLM Integration and AI-powered Web Applications

Key Responsibilities & Required Skills

• 1. AI Application Development: Design, develop and integrate AI-powered processes and intelligent features into web applications using industry-standard AI frameworks, tools and libraries.
• 2. Programming & API Development: Strong hands-on experience in Python and Node.js for developing AI services, backend integrations, APIs, automation workflows and AI-driven application components. Proven experience building high-performance REST APIs and AI microservices using FastAPI (Python) and Express.js (Node.js), including request/response validation, asynchronous processing, authentication, OpenAPI/Swagger documentation, and serving ML/LLM models as scalable API endpoints.
• 3. Machine Learning, Deep Learning & NLP: Solid foundation in Machine Learning, Deep Learning and Natural Language Processing, with hands-on experience in data preparation, feature engineering, model training, fine-tuning and evaluation. Practical experience with NLP tasks such as text classification, named entity recognition, information extraction, summarization, semantic search and sentiment analysis, using libraries such as scikit-learn, PyTorch, TensorFlow/Keras, Hugging Face Transformers, spaCy and NLTK.
• 4. Generative AI & LLM Integration: Practical experience working with LLMs such as OpenAI GPT, Google Gemini, Anthropic Claude, Llama and other open-source or commercial AI models.
• 5. AI Frameworks & Libraries: Experience with industry-standard Generative AI frameworks and libraries such as LangChain, LangGraph, LlamaIndex, Hugging Face and relevant AI/ML ecosystems.
• 6. AI Model Evaluation & Selection: Ability to evaluate different AI adoption approaches, models and architectures, assess their suitability against business requirements, and recommend cost-effective and scalable solutions.
• 7. End-to-End AI Implementation: Ability to independently drive AI adoption from requirement analysis and solution design to POC development, model evaluation, integration, deployment and production rollout.
• 8. POC to Production-grade Development: Strong capability to convert experimental AI prototypes into reliable, secure, scalable and maintainable production-grade solutions, including error handling, performance optimization and monitoring.
• 9. AI Integration & Architecture: Experience integrating AI capabilities with existing web applications, REST APIs, databases and enterprise systems. Understanding of AI agents, workflow automation, function/tool calling and orchestration is desirable.
• 10. Responsible AI & Continuous Improvement: Understanding of AI security, data privacy, prompt engineering, hallucination mitigation, model limitations, token/cost optimization and continuous evaluation of AI-powered processes.

Good to Have

• Exposure to additional AI adoption approaches such as Computer Vision and Agentic AI.
• Exposure to Docker, Kubernetes and CI/CD for deploying and managing AI services.
• Experience with vector databases such as PostgreSQL with pgvector, Pinecone, Weaviate or Milvus.