Artificial Intelligence Engineer

Khatib & Alami; Bengaluru; On-site; INR 3,000,000 - 5,500,000; Full time

Job summary

Khatib & Alami is seeking an experienced AI Engineer to design, develop, and deploy agentic AI solutions for enterprise-scale workflows. You will architect multi-agent systems, integrate with enterprise platforms, and ensure secure, scalable AI deployments across the organization.

You will collaborate with IT, cybersecurity, data, and engineering teams to translate business needs into practical AI apps, with a strong emphasis on governance, observability, and responsible AI practices.

Qualifications

• 3–7+ years in software engineering, AI/ML, data engineering, or related field.
• Strong programming skills in Python.
• Hands-on experience with LLMs, AI agents, and agentic workflows.

Responsibilities

• Design and develop single-agent and multi-agent AI solutions for enterprise business processes.
• Build agent architectures using LLMs, tool calling, workflows, memory, planning, reasoning, and RAG.
• Develop AI applications, copilots, assistants, and intelligent automation integrated into existing processes.
• Identify opportunities to automate repetitive activities across proposal and tender prep, QA/QC, project management, document control, contracts, finance, procurement, HR, and IT service management.
• Develop secure integrations between AI agents and enterprise platforms via APIs, SDKs, web services, databases, and automation frameworks.
• Build RAG and knowledge-engineering pipelines, including document ingestion, chunking, embeddings, metadata, indexing, retrieval, and reranking.
• Develop production-quality AI solutions using Python, including APIs, microservices, backend services, and orchestration components.
• Implement testing, CI/CD, version control, monitoring, logging, observability, and scalable deployment practices.
• Apply governance, security, audit, privacy, and responsible AI controls, including safeguards against prompt injection and data leakage.
• Establish evaluation frameworks and continuously improve AI-agent accuracy, reliability, latency, cost efficiency, user adoption, and business outcomes.
• Collaborate with business, IT, engineering, cybersecurity, data, and functional teams to translate requirements into practical AI solutions.
• Contribute to reusable AI platforms, standards, architecture patterns, and engineering practices.

Skills

Python

LLM APIs & SDKs

Prompt engineering

RAG

Vector databases

Agent orchestration

Workflow automation

APIs & integration

REST APIs

Git

Docker

AI evaluation

Observability

Education

Degree in CS/AI/SE

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Kubernetes

Azure

AWS

GCP

Job description

Job Summary

The AI Engineer will design, develop, integrate, and deploy AI-powered applications and autonomous AI agents that improve business productivity, automate complex workflows, and enhance decision-making across the organization.

The role focuses on Agentic AI, building secure and scalable AI agents that can reason through tasks, retrieve and process information, interact with enterprise systems and tools, collaborate with other agents, and execute multi-step workflows with appropriate human oversight.

Key Responsibilities

• Design and develop single-agent and multi-agent solutions for enterprise business processes.
• Build agent architectures using LLMs, tool calling, workflows, memory, planning, reasoning, and retrieval-augmented generation (RAG).
• Develop AI applications, copilots, assistants, and intelligent automation solutions integrated into existing business processes.
• Identify opportunities to automate or augment repetitive activities across proposal and tender preparation, engineering QA/QC, project management, document control, contracts, finance, procurement, HR, and IT service management.
• Develop secure integrations between AI agents and enterprise platforms through APIs, SDKs, web services, databases, and automation frameworks.
• Build RAG and knowledge-engineering pipelines, including document ingestion, chunking, embeddings, metadata, indexing, retrieval, and reranking.
• Develop production-quality AI solutions using Python, including APIs, microservices, backend services, and orchestration components.
• Implement testing, CI/CD, version control, monitoring, logging, observability, and scalable deployment practices.
• Apply appropriate governance, security, audit, privacy, and responsible AI controls, including safeguards against prompt injection, data leakage, and unauthorized actions.
• Establish evaluation frameworks and continuously improve AI-agent accuracy, reliability, latency, cost efficiency, user adoption, and business outcomes.
• Collaborate with business, IT, engineering, cybersecurity, data, and functional teams to translate business requirements into practical AI solutions.
• Contribute to reusable AI platforms, standards, architecture patterns, and engineering practices.

Required Qualifications

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Software Engineering, Data Science, Engineering, or a related discipline.
• 3–7+ years of experience in software engineering, AI/ML, data engineering, or a related field, depending on seniority.
• Strong programming skills in Python.
• Strong understanding of LLMs, Generative AI, APIs, databases, distributed systems, and software architecture.
• Hands-on experience building applications using LLM APIs, AI agents, AI workflows, or agentic applications.
• Experience with Git, CI/CD, testing, and modern software-development practices.
• Understanding of cloud or private-cloud deployment architectures.

Technical Skills

Essential

Python, LLM APIs and SDKs, prompt engineering, RAG, vector databases, agent orchestration, tool/function calling, workflow automation, API development and integration, REST APIs, SQL, Git, Docker, AI evaluation, and observability.

Desirable

LangGraph, LangChain, LlamaIndex, Semantic Kernel, MCP, Kubernetes, Azure, AWS, GCP or private-cloud platforms, knowledge graphs, multimodal AI, computer vision, OCR/document intelligence, event-driven architectures, SAP integration, SharePoint/Microsoft Graph, Autodesk Construction Cloud/BIM 360 APIs, and enterprise document-management systems.

Ideal Profile

The successful candidate will be a strong software engineer who can combine LLMs, enterprise data, APIs, workflows, and business processes to build reliable AI agents that perform meaningful work.

Experience within engineering, EPC, construction, or another complex enterprise environment, including systems such as SAP S/4HANA, SAP SuccessFactors, SAP Cloud for Customer, Microsoft SharePoint, Autodesk Construction Cloud/BIM 360, or enterprise project and document-management platforms, will be a significant advantage.