Artificial Intelligence Engineer

Khatib & Alami; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Khatib & Alami is seeking a senior software engineer to design and deliver enterprise AI solutions integrating LLMs, AI agents, and orchestrated workflows. You will work across business, IT, cybersecurity, and engineering to translate requirements into practical AI systems that scale in complex enterprise environments.

The role emphasizes robust software engineering practices, governance, and secure integration with enterprise platforms such as SAP, SharePoint, and document-management systems.

Qualifications

• Bachelor’s or Master’s degree in CS, AI, software engineering or related field.
• 3–7+ years in software engineering, AI/ML, data engineering, or related field.
• Strong Python programming skills.
• 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.

Responsibilities

• Design and develop single-agent and multi-agent solutions for enterprise 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.

Skills

Python

LLMs

APIs

Databases

Distributed systems

Software architecture

Git

CI/CD

Testing

Cloud deployment

Agentic applications

Education

Bachelor’s or Master’s degree in CS/AI/Software Eng/Data Science or related

Tools

LangGraph

LangChain

LlamaIndex

Semantic Kernel

MCP

Kubernetes

Azure

AWS

GCP

SAP integration

SharePoint/Microsoft Graph

Autodesk Construction Cloud/BIM 360 APIs

Job description

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

• Bachelor’s or Master’s 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

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.

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.