AI Backend Engineer

Gleantap; Amritsar; On-site; INR 1,200,000 - 2,500,000; Full time

Job summary

Gleantap is seeking a strong backend engineer to enhance the PHP backend while building AI-powered capabilities for our SaaS product. You will ship production software, work with real customer data, and apply AI/LLMs practically in a fast-paced environment.

The role involves implementing AI agents, RAG-based systems, and data pipelines, using LangChain and vector databases, with a focus on reliability and scalability.

Qualifications

• Strong backend development experience.
• Hands-on experience with PHP.
• Strong experience with Python.
• Experience building APIs, backend services, and data-driven applications.
• Practical experience working with LLM APIs such as OpenAI, Anthropic Claude, Gemini, or similar.
• Understanding of AI agent concepts, prompt engineering, function calling, and structured AI outputs.
• Experience with embeddings, vector search, RAG, or vector databases.
• Familiarity with LangChain, LlamaIndex, or similar frameworks.
• Strong SQL skills and comfort working with relational databases.
• Understanding of ETL concepts, data pipelines, data cleaning, and transformation.
• Familiarity with core machine learning concepts such as classification, prediction, embeddings, model evaluation, training vs inference, and feature engineering.
• Ability to debug production issues and work in an existing codebase.

Responsibilities

• Build, maintain, and improve backend features in our existing PHP application.
• Develop AI agents and automation workflows using Python.
• Integrate LLMs into product features.
• Build RAG-based systems with embeddings and vector databases.
• Work with LangChain, LlamaIndex, or similar AI orchestration libraries.
• Design APIs, backend services, and data processing workflows.
• Build and maintain ETL pipelines to move, clean, transform, and structure data.
• Handle data from CRMs, conversations, customer records, emails, websites, and integrations.
• Implement prompt pipelines, tool calls, intent classification, memory, and agent workflows.
• Collaborate with product, engineering, and leadership to turn business problems into AI features.
• Monitor, debug, and improve AI output quality, latency, cost, and reliability.
• Write clean, maintainable, testable code.
• Support integrations with third-party APIs and internal systems.
• Help modernize parts of the backend architecture over time.

Skills

PHP

Python

LLM APIs

SQL

Vector DB

LangChain

API design

ETL pipelines

Debug production

Tools

OpenAI API

Anthropic Claude API

Job description

About the Role

We are looking for a strong backend engineer who can work across our existing PHP backend while helping us build the next generation of AI-powered product capabilities.

This is not a pure AI research role. We need someone who can ship production software, work with real customer data, build reliable backend systems, and apply AI/LLMs practically inside a SaaS product.

You will work on core backend development in PHP, build AI agents and automation workflows in Python, integrate LLMs and vector databases, and support data pipelines, ETL processes, and ML-driven product features.

The ideal candidate is a hands-on engineer who is comfortable maintaining existing systems while also building new AI-native capabilities from the ground up.

Responsibilities

• Build, maintain, and improve backend features in our existing PHP application.
• Develop AI agents and automation workflows using Python.
• Integrate LLMs such as OpenAI, Claude, Gemini, or similar models into product features.
• Build RAG-based systems using embeddings, vector databases, and document retrieval.
• Work with frameworks and tools such as LangChain, LlamaIndex, or similar AI orchestration libraries.
• Design APIs, backend services, background jobs, and data processing workflows.
• Build and maintain ETL pipelines to move, clean, transform, and structure data.
• Work with structured and unstructured data from CRMs, conversations, customer records, emails, websites, and third-party integrations.
• Implement prompt pipelines, tool/function calling, intent classification, memory, and agent workflows.
• Collaborate with product, engineering, and leadership to turn business problems into AI-powered features.
• Monitor, debug, and improve AI output quality, latency, cost, and reliability.
• Write clean, maintainable, testable code.
• Support integrations with third-party APIs and internal systems.
• Help modernize parts of the backend architecture over time.

Required Skills

• Strong backend development experience.
• Hands-on experience with PHP.
• Strong experience with Python.
• Experience building APIs, backend services, and data-driven applications.
• Practical experience working with LLM APIs such as OpenAI, Anthropic Claude, Gemini, or similar.
• Understanding of AI agent concepts, prompt engineering, function calling, and structured AI outputs.
• Experience with embeddings, vector search, RAG, or vector databases.
• Familiarity with LangChain, LlamaIndex, or similar frameworks.
• Strong SQL skills and comfort working with relational databases.
• Understanding of ETL concepts, data pipelines, data cleaning, and transformation.
• Familiarity with core machine learning concepts such as classification, prediction, embeddings, model evaluation, training vs inference, and feature engineering.
• Ability to debug production issues and work in an existing codebase.
• Strong problem-solving ability and ownership mindset.

Nice to Have

• Experience with CodeIgniter, Laravel, or other PHP frameworks.
• Experience with Node.js or React.
• Experience with queue systems, cron jobs, workers, webhooks, and background processing.
• Experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, Qdrant, or pgvector.
• Experience with CRM, marketing automation, customer support, or messaging platforms.
• Experience with voice AI, chatbots, customer service automation, or sales automation.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Experience with data warehouses, analytics pipelines, or BI tools.
• Experience with model evaluation, AI guardrails, observability, and cost optimization.