Technical Solutions Delivery Manager - AI - Chandigarh

Mset; Chandigarh; On-site; INR 1,500,000 - 2,000,000; Full time

Benefits offered by this job

Access to AI training and certifications

Flexible working arrangements

Competitive compensation package

Job summary

Mset in Chandigarh is looking for a Technical Solutions Delivery Manager to drive AI strategy and oversee solution architecture. In this senior leadership role, you will bridge the gap between strategic AI vision and practical implementation, leading engagements with enterprise clients.

You will ensure alignment with technical and business objectives while mentoring teams and guiding AI transformation initiatives. The position supports flexible working and offers competitive compensation.

Qualifications

• Hands-on experience with Agentic AI tools that improved team efficiency.
• Proven experience defining and executing AI strategy at an organizational level.
• Experience embedding AI agents across SDLC processes.
• Strong understanding of cloud-native architecture patterns on Azure.
• Deep knowledge of CI/CD and automated testing strategies.

Responsibilities

• Own end-to-end solution architecture for AI strategy.
• Lead technical discovery and presales activities with clients.
• Design reference architectures for mobile and backend integration.
• Mentor Engineering Leads on architecture best practices.
• Represent engineering function in steering committees.

Skills

Agentic AI tools

AI strategy execution

Mobile application architecture

Cloud-native architecture

DevOps best practices

Tools

Jira

Confluence

Job description

# Technical Solutions Delivery Manager - AI - ChandigarhChandigarhCompetitive SalaryWe are seeking a Technical Solutions Delivery Manager with deep technical expertise and a proven track record of defining and executing AI strategy within large-scale technology delivery programmes. This is a senior leadership role bridging strategic AI vision with hands-on solutioning – you will own the end-to-end solution architecture, lead technical presales and discovery, and shape the AI transformation roadmap for enterprise clients.The ideal candidate has personally created AI strategies in previous organisations – from gap analysis and use-case identification through to phased implementation roadmaps, governance frameworks, and value realisation tracking. You are equally comfortable presenting to C-suite executives and whiteboarding architecture with engineers.You will operate across client-facing and internal contexts: leading solution design for new engagements, defining reference architectures, mentoring engineering leads, and championing an Agentic AI-first delivery culture across the organisation.Apply for this role## What you'll doOwn end-to-end solution architecture for complex, multi-market mobile and digital loyalty platforms, ensuring alignment with client business objectives and technical constraintsDefine and drive AI strategy across the SDLC – identifying automation opportunities, building use-case roadmaps aligned to PI cadence (e.g., AMJ, JAS, OND), and establishing governance for AI adoptionLead technical discovery, presales, and solutioning activities with enterprise clients, translating business challenges into structured delivery proposalsDesign reference architectures for mobile (iOS, Android, Flutter, React Native), backend (.NET, Node.js), cloud (Azure AKS, Web Apps), and AI agent integration (LangChain, CrewAI, Claude)Conduct solution reviews, architecture governance, and technical risk assessments across delivery squadsMentor and coach Engineering Leads and Senior Engineers on architecture best practices, AI tool adoption, and technical decision-makingDefine non-functional requirements (performance, scalability, security, accessibility) and ensure they are embedded in delivery from sprint zeroRepresent the engineering function in programme-level steering committees, PI planning events, and client-facing reviews## What you'll bring[MANDATORY] Hands-on experience with Agentic AI tools or advanced AI-assisted workflows (e.g., AI-driven code generation, autonomous testing agents, AI-powered architecture review, Claude, Cursor, Copilot Workspace) that have demonstrably improved personal or team efficiency by 150–200%. Candidates must demonstrate specific examples during the interview processProven experience defining and executing AI strategy at an organisational or programme level – including gap analysis, use-case prioritisation, phased roadmaps, governance frameworks, and ROI trackingExperience embedding AI agents across SDLC processes: requirements decomposition, design-to-code pipelines, automated test generation, intelligent deployment, and monitoringDeep understanding of LLM capabilities, prompt engineering, RAG pipelines, and AI agent orchestration patterns (tool use, multi-step reasoning, autonomous task completion)Ability to build AI maturity assessments and capability roadmaps for engineering organisationsExtensive experience architecting mobile applications at enterprise scale across iOS, Android, and cross-platform frameworks (Flutter / React Native)Strong understanding of cloud-native architecture patterns (microservices, event-driven, serverless) on Azure or equivalent platformsExperience with enterprise loyalty, rewards, or commerce platforms serving multiple markets with configuration-driven personalisationDeep knowledge of CI/CD, automated testing strategies, security tooling, and DevOps best practicesExperience with technical presales, RFP responses, estimation, and solution proposal developmentProficiency with Jira, Confluence, and programme-level delivery artefacts within PI planning frameworks (SAFe or equivalent)## Nice to haveExperience with Server-Driven UI (SDUI) patterns and multi-market configuration management architecturesBackground in building or scaling engineering consultancies / capability practicesPublished thought leadership, conference talks, or internal whitepapers on AI in engineering deliveryFamiliarity with Azure AI services (OpenAI, Cognitive Services, ML Studio) or equivalentExperience with AI-focused frameworks: LangChain, LangGraph, CrewAI, Semantic Kernel, or AutoGen## Benefits & PerksOpportunity to work on a globally recognised consumer brandAn AI-first engineering culture that invests in cutting-edge tools and continuous learningCollaborative, distributed team environment spanning multiple geographiesCompetitive compensation package with performance-based progressionAccess to AI training, certifications, conference attendance, and dedicated innovation timeFlexible working arrangements with a focus on outcomes over hours### Role summaryLocation: ChandigarhType: Full-timeCompensation: Competitive Salary