Senior AI Engineer

Kagool; India; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Kagool seeks a Senior AI Engineer to lead design and delivery of enterprise AI and GenAI solutions. You will stay hands-on while guiding engineers, making architectural decisions and ensuring production-grade security, reliability and scalability on Azure.

You will own multi‑agent workflow design, LLMOps practices, and integration with enterprise data sources, APIs and cloud services, while mentoring teammates and balancing delivery risk with quality.

Qualifications

• 8–13 years of software engineering experience with hands-on AI/ML and GenAI delivery.
• Strong Python, SQL, backend engineering and system design skills.
• Proven experience with LLMs, RAG, embeddings, prompt engineering and evaluation.
• Practical experience building agentic or multi-agent systems using LangGraph, LangChain or equivalents.

Responsibilities

• Own solution design and technical delivery for conversational AI, RAG apps and agentic systems.
• Define retrieval architectures using vector/search and graph databases; implement scalable AI services on Azure.
• Lead design reviews, mentor engineers, and translate business needs into robust technical solutions.

Skills

Python

LLM/GenAI

System design

Back-end

SQL

Communication

Mentoring

Tools

LangGraph

LangChain

Azure OpenAI

Azure AI Search

PyTorch

TensorFlow

Databricks

Spark

Neo4j

Job description

We are looking for a Senior AI Engineer to lead the technical design and delivery of enterprise AI and Generative AI solutions. You will remain hands‑on while guiding engineers, making architecture decisions and ensuring solutions are secure, reliable and ready for production. Kagool is a fast‑growing IT consultancy specializing in the transformation of complex global enterprises. We are looking for passionate and hardworking individuals to help deliver for our global customer base. We embrace the opportunities of the future and work proactively to make good use of technology.

Own solution design and technical delivery for conversational AI, RAG applications and agentic systems. Design and implement multi‑agent workflows covering planning, retrieval, tool execution, memory and evaluation. Define retrieval architectures using vector search, hybrid search and, where appropriate, graph databases. Build and integrate scalable AI services with enterprise applications, APIs and cloud platforms, primarily Azure. Establish LLMOps practices covering prompt and model versioning, CI/CD, automated evaluation, monitoring and regression testing. Implement access controls, auditability, privacy safeguards and responsible AI guardrails. Optimise accuracy, latency, reliability and cost using production metrics and user feedback. Translate business requirements into technical solutions, lead design and code reviews, and mentor engineers.

8–13 years of software engineering experience, including substantial hands‑on AI/ML experience and delivery of production GenAI solutions.

Strong Python, SQL, backend engineering and system design skills.

Proven experience with LLMs, RAG, embeddings, prompt engineering and evaluation.

Practical experience designing agentic or multi‑agent systems using LangGraph, LangChain or equivalent frameworks.

Strong experience with vector databases, enterprise search and structured/unstructured data integration.

Experience deploying and operating cloud applications, preferably using Azure OpenAI, Azure AI Search and related Azure services.

Working knowledge of containers, CI/CD, observability and MLOps/LLMOps. Ability to make technical trade‑offs, manage delivery risks and communicate clearly with business and technical stakeholders.

Preferred:

• Experience with Databricks, Spark, Neo4j, Document Intelligence, event‑driven integration, model fine‑tuning or frameworks such as PyTorch and TensorFlow.