AI Engineer

Crisil; India; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Mashreq is seeking an experienced AI Engineer to design, build, test, and operate enterprise AI capabilities including Generative AI, cognitive agents, and the AI CoE platforms.

You will implement Python‑based services, integrate Azure OpenAI and related Microsoft Azure components, and ensure secure, observable, and scalable AI solutions across the organization.

Qualifications

• 5–7 years in software, data, ML, or AI engineering with enterprise delivery.
• Hands‑on GenAI, LLMs, prompt engineering, RAG, AI agents, multi‑agent systems.
• Hands‑on Azure AI including OpenAI, Foundry, Search, Functions, AKS, API Management, Fabric.

Responsibilities

• Design, build, test, and operate enterprise AI capabilities and platforms.
• Develop Python‑based AI services, prompts, RAG pipelines, and agents.
• Configure Azure OpenAI, Foundry, Search, Functions, AKS, API Management, Fabric.
• Monitor quality, latency, safety, and cost; support controlled production releases.
• Produce maintainable code, docs, and runbooks.

Skills

Python

LLM application development

Prompt engineering

RAG

AI agents

Multi-agent systems

Tool calling

Function calling

Automated evaluation

Agile delivery

Education

Bachelor’s degree in Computer Science, AI, Data Science, IT, Engineering or related

Tools

Azure OpenAI

Azure AI Foundry

Azure AI Search

Azure Functions

AKS

Azure API Management

Microsoft Fabric

Git and CI/CD

Job description

Role Purpose

Design, build, test, and operate enterprise AI and Generative AI capabilities supporting Mashreq’s AI CoE, Agentic AI Ecosystem, Enterprise AI Platform, and Trade Virtual Assistant. The role delivers secure, reusable, and observable AI services aligned with Mashreq’s AI Strategy, engineering standards, and digital transformation priorities.

Key Responsibilities

Strategic Responsibilities

• Contribute to reusable AI engineering patterns, platform accelerators, and technical standards.
• Assess suitable LLM, RAG, agent, MCP, tool-calling, and function-calling approaches against business and non‑functional needs.

Delivery Responsibilities

• Develop Python-based AI services, prompt workflows, RAG pipelines, embeddings, retrieval, AI agents, and multi‑agent components.
• Configure and integrate Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, AKS, Azure API Management, and Microsoft Fabric.
• Implement APIs, tool integrations, function calling, data connectors, automated tests, evaluation datasets, CI/CD, and MLOps pipelines.
• Monitor quality, latency, reliability, safety, and cost; investigate defects and support controlled production releases.
• Produce maintainable code, technical documentation, deployment instructions, and operational runbooks.

Governance Responsibilities

• Apply Responsible AI, security, privacy, compliance, access-control, content‑safety, and data‑handling requirements.
• Maintain traceability for prompts, models, retrieval sources, evaluations, changes, and releases.
• Support architecture, security, risk, and governance reviews and remediate identified control gaps.

Stakeholder Management Responsibilities

• Work with the Senior AI Engineer, AI Architect, product owners, business analysts, data teams, platform teams, and vendors.
• Explain engineering progress, dependencies, risks, and technical choices clearly to delivery stakeholders.

Required Experience

• 5–7 years in software, data, ML, or AI engineering with hands‑on enterprise delivery.
• Practical experience with GenAI, LLMs, prompt engineering, RAG, AI agents, multi‑agent systems, MCP, tool calling, and function calling.
• Hands‑on Azure AI experience including Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, AKS, Azure API Management, and Microsoft Fabric.
• Experience with Python, APIs, containers, CI/CD, MLOps, observability, testing, and enterprise integration.
• Banking or financial‑services exposure preferred, including retail, corporate, trade finance, digital banking, risk, or compliance.

Required Skills

• Python; LLM application development; Prompt engineering; RAG; AI agents; Multi‑agent systems; MCP; Tool calling; Function calling; Automated evaluation
• Azure OpenAI; Azure AI Foundry; Azure AI Search; Azure Functions; AKS; Azure API Management; Microsoft Fabric; Git and CI/CD
• REST APIs; Data connectors; Event integration; Authentication and authorization; Enterprise application integration
• Responsible AI; AI governance; Security and compliance; MLOps; Observability; Model and prompt monitoring; Enterprise standards
• Problem solving; Agile delivery; Documentation; Collaboration; Clear stakeholder communication

Preferred Tools and Certifications

• Microsoft Certified: Azure AI Engineer Associate
  Build and deploy AI solutions on Microsoft Azure.
• Microsoft Certified: Azure Fundamentals
  Demonstrate foundational Azure cloud knowledge.
• Generative AI Certification
  Apply LLM, prompt, RAG, and responsible GenAI practices.
• Python Certification
  Demonstrate applied Python programming capability.

Education

Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, Engineering, or a related discipline is mandatory. A Master’s degree is preferred.