What You'll Do

- Design and develop complex backend and AI-driven solutions from scratch .

- Build scalable backend services using Node.js and Python .

- Develop and integrate LLM/Generative AI models into real-world enterprise workflows.
- Build AI agents, RAG pipelines, intelligent workflows, semantic search, and AI automation .

- Work with both open-source and commercial LLMs , including model experimentation, evaluation, optimization, and deployment.

- Design and implement solutions using Vector Databases and Graph Databases for intelligent data retrieval and relationship-based reasoning.
- Develop knowledge graphs and data relationships across manufacturing and enterprise data.

- Work on AI-powered document processing and OCR-based systems for documents such as Customer POs, invoices, delivery schedules, and other business documents.
- Work on IoT integrations to connect machines, devices, sensors, and industrial systems with the Dharte AI platform.

- Develop APIs and services for communication between AI systems, backend services, IoT devices, and the core ERP platform.
- Design complex business logic involving production, procurement, inventory, quality, maintenance, and manufacturing workflows

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- Work with relational and non-relational data and design efficient data models for AI applications.
- Evaluate and improve AI systems based on accuracy, latency, reliability, scalability, and inference cost .

- Deploy and maintain AI services in development, staging, and production environments.
- Collaborate with Product, Backend, Frontend, and Manufacturing teams to convert business requirements into working AI solutions.

Required Skills

Backend Engineering





- Strong hands-on experience with Node.js and Python .

- Robust understanding of REST APIs, microservices, authentication, asynchronous processing, and backend architecture.
- Ability to design and build complex application logic from scratch .

- Strong knowledge of PostgreSQL / relational databases .

- Valuable understanding of system design and scalable application architecture.

AI / LLM

- Strong practical knowledge of Generative AI and Large Language Models (LLMs) .

- Experience building applications using LLMs rather than only consuming basic AI APIs.
- Experience with RAG, embeddings, prompt engineering, AI agents, tool calling, and semantic search .

- Experience working with frameworks such as LangChain, LlamaIndex, or equivalent .

- Experience with open-source models such as Llama, Qwen, Mistral, etc. is highly valuable.

- Understanding of model evaluation, context management, hallucination reduction, and AI system optimization.

Databases & Data

- Hands-on experience with at least one Vector Database such as Qdrant, Pinecone, Weaviate, Milvus, pgvector, etc.

- Understanding of Graph Databases such as Neo4j or equivalent.
- Experience designing relationships between complex business entities and using graph-based data for AI applications.

- Understanding of data pipelines, embeddings, indexing, retrieval,



and knowledge representation.

IoT & Integrations

- Hands-on experience with IoT integration and communication between devices/machines and software platforms.

- Understanding of protocols such as MQTT, HTTP, WebSockets, OPC-UA, Modbus , or similar will be an advantage.

- Experience working with machine/device data, sensor data, telemetry, or industrial systems is highly preferred.

Good to Have
- Experience in Manufacturing / Industrial Automation / ERP / MES / IIoT .

- Experience with OCR and document intelligence .

- Experience with Speech-to-Text / Audio AI .

- Experience deploying self-hosted LLMs using technologies such as Ollama or similar.
- Experience with GPU-based model inference and optimization .

- Experience with Docker and cloud infrastructure.
- Experience building AI systems that operate on structured + unstructured enterprise data .

- Knowledge of Computer Vision.
- Familiarity with event-driven architectures and real-time data processing.

Who We're Looking For We are looking for an engineer who is comfortable going beyond predefined tasks.

You should be able to take a problem from requirement → architecture → database/data design → backend logic → AI implementation → integration → deployment

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The ideal candidate should be someone who enjoys building things from the ground up

, experimenting with new AI technologies, solving complex engineering problems, and turning AI concepts into reliable production features.

If you are excited about combining AI, backend engineering, IoT, and manufacturing automation to build a real-world AI product, we'd love to hear from you.

📌 Artificial Intelligence Engineer (Dehradun)
🏢 Dharte AI
📍 Dehradun