About the role

Job Description:

Senior AI Engineer — AI & Intelligent Solutions

Location- Remote

Budget- 1.5 LPM

About the Role

We are seeking a highly skilled and experienced Senior AI Engineer to join our growing AI & Digital Innovation team. The successful candidate will play a central role in the design and development of enterprise-grade AI solutions, with a focus on building scalable, extensible platforms that support both conversational and transactional AI capabilities across multiple business functions.

This is a hands-on technical role suited to an engineer who combines deep AI implementation experience with the ability to lead technically, influence architecture decisions, and collaborate effectively with cross-functional teams. The ideal candidate is passionate about applied AI, has a strong engineering foundation, and has demonstrated experience delivering AI solutions in complex enterprise environments.

Key Responsibilities

AI Solution Design & Development

Design, develop, and maintain scalable AI solutions that support both conversational (chat-based) and transactional business functions
Contribute to the architecture of AI platforms that are modular and extensible, enabling adoption across multiple business units with varying requirements
Evaluate and recommend appropriate AI tools, models, frameworks, and platforms based on use case requirements and organisational standards
Implement orchestration patterns that coordinate AI agents, models, and workflows in a coherent and reliable manner

AI Integration & Engineering

Build and maintain integrations between AI components and enterprise systems including CRM, ERP, document management, HR platforms, and communication tools
Design and implement APIs and integration patterns that enable seamless connectivity between AI capabilities and consuming applications
Implement Retrieval-Augmented Generation (RAG) pipelines, agentic workflows, and multi-model coordination patterns based on solution requirements
Ensure AI solutions are engineered for performance, reliability, and maintainability in production environments

Conversational & Transactional AI

Develop conversational AI capabilities including intelligent chatbots, virtual assistants, and LLM-powered dialogue systems
Build transactional AI functions that automate or augment business processes such as document processing, data retrieval, approvals, and workflow automation
Support the design of solutions that handle both real-time and batch AI processing depending on the nature of the business use case

Governance, Security & Responsible AI

Apply responsible AI principles throughout the development lifecycle including fairness, transparency, explainability, and data privacy
Adhere to and contribute to AI governance practices covering model versioning, monitoring, and auditability
Ensure AI solutions are built in compliance with organisational security policies, data handling standards, and relevant regulatory requirements
Collaborate with the Information Security team to embed appropriate controls within AI solution design

Technical Leadership & Collaboration

Serve as a technical lead within the AI team, providing guidance and mentorship to junior engineers and developers
Work closely with solution architects, business analysts, and product owners to translate business requirements into sound technical designs
Participate in design reviews, technical discussions, and proof-of-concept evaluations
Contribute to the development of internal standards, engineering guidelines, and reusable AI components
Stay current with advancements in the AI space and proactively identify opportunities to apply emerging capabilities within the organisation

Required Qualifications & Experience

Education

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical discipline

Experience

Minimum 4–6 years of overall experience in software or AI engineering
Minimum 3 years of hands-on experience designing and implementing production AI solutions in an enterprise environment
Proven experience working on AI platforms or solutions that span conversational and process automation use cases
Experience contributing to or leading the technical delivery of AI integration projects involving multiple enterprise systems

Technical Skills

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Area	Required Expertise
AI & ML Frameworks	LangChain, Semantic Kernel, AutoGen, LlamaIndex, or equivalent AI orchestration frameworks
Large Language Models	OpenAI GPT, Azure OpenAI, Anthropic Claude, Gemini, or open-source LLMs (LLaMA, Mistral)
Vector Databases	Pinecone, Weaviate, Azure AI Search, pgvector, or equivalent
Cloud — Azure (Primary)	Azure OpenAI Service, Azure AI Studio, Azure Bot Services, Azure API Management, Azure Functions, Azure Logic Apps
Azure Infrastructure	Azure Kubernetes Service (AKS), Azure Container Apps, Azure Service Bus, Azure Key Vault, Azure Monitor
Programming Languages	Python (primary), with working proficiency in at least one of JavaScript, C#, or Java
API & Integration	REST API design, event-driven architecture, webhook patterns, API gateway management
RAG & Knowledge Retrieval	Retrieval-Augmented Generation (RAG), embedding models, semantic search, knowledge base integration
Security & Governance	AI security controls, data privacy compliance, responsible AI principles
DevOps & MLOps	CI/CD pipelines, containerisation (Docker, Kubernetes), model versioning, prompt management, and monitoring

Preferred Qualifications

Hands-on experience with the Microsoft Azure AI and integration stack, including Azure AI Studio, Azure Integration Services, and Azure API Management
Familiarity with agentic AI design patterns and multi-agent coordination frameworks
Experience working in regulated industries such as aviation, finance, healthcare, or government
Exposure to enterprise integration platforms such as MuleSoft, Azure Integration Services, or equivalent middleware
Microsoft Azure certifications such as Azure AI Engineer Associate (AI-102) or Azure Developer Associate (AZ-204) are an advantage
Familiarity with Power Platform (Power Automate, Power Apps) in the context of AI-assisted workflows

Key Competencies

Technical Depth — Strong hands-on engineering capability with the ability to move from concept to working solution
Problem Solving — Approaches complex and ambiguous technical challenges in a structured and pragmatic manner
Communication — Able to explain technical concepts and decisions clearly to both technical peers and non-technical stakeholders
Collaboration — Works well within cross-functional teams and across business units with differing priorities
Innovation Mindset — Actively follows developments in the AI space and brings relevant ideas and approaches to the team
Ownership — Takes responsibility for the quality and reliability of solutions developed and proactively addresses issues
Mentorship — Committed to uplifting team capability through knowledge sharing and hands-on guidance