Principal Deployment Architect

Highlight of the engagement opportunity: - Nature of role: Full time - Number of years of experience expected: 7-10 years. - Areas of past experience preferred: Enterprise software deployment, Solution architecture, Cloud infrastructure, Professional services, Client Management. - Educational qualification required: Bachelors / Masters degree in Engineering (Preferably Computer Science). - Additional certifications preferred: Certifications on Azure, AWS, Kubernetes, Containers, Networking, Security, and Enterprise infrastructure. - Preferred geography of previous work experience: India / Europe / APAC / US. - Language requirements: Ability to write and speak fluently in English. - Technology proficiency preferred: Azure, AWS, Kubernetes, Containers, Networking, Security, and Enterprise infrastructure. Key responsibility areas: - Lead the end-to-end deployment of Acies platforms and applications across enterprise customers. - Own deployment architecture, infrastructure design, and implementation best practices. - Act as the primary technical advisor for customers during onboarding, deployment, and production rollout. - Lead and mentor the Deployment Engineering team, establishing standards, processes, and delivery excellence. - Conduct technical workshops with customer IT, Security, Cloud, and Architecture teams. - Design scalable deployment models across cloud, on-premises, and hybrid environments. - Develop Statements of Work (SOWs), deployment plans, implementation roadmaps, and technical documentation. - Support Sales and Customer Success teams in technical discovery, solution design, and enterprise deal cycles. - Drive adoption of managed infrastructure, deployment, and operational services. - Own technical risk management, deployment governance, and escalation resolution for strategic customers. Other important information: - Work permit requirements: Either Indian Citizen or having valid work permit to work in India. - Period of engagement: Full-time position. - Probation period: 6 months. - Compensation: Compensation varies depending on the skill, fitment and role played by the person. Compensation discussions will take place post the selection process. - Performance incentives: Typically, all roles at Acies have a performance incentive. Specific aspects will be discussed during the compensation discussion. - Leave: 19 working days a year. Additional leaves for national holidays, sick leaves, maternity and paternity, bereavement and studies vary based on the city and country of engagement. - Other benefits: Other employment benefits including medical insurance will be informed during the compensation discussion. - Career growth for full-time roles: Acies believes in a transparent and data-based performance evaluation system. You are encouraged to clarify any questions you have with respect to career growth with Acies personnel you interact with during the selection process. - Career opportunities for part-time roles: Conversion of part-time roles to full-time roles depends on both performance of the individual and business needs. You are encouraged to ask about the prospects as you interact with Acies personnel during the selection process. - Global mobility: Acies encourages mobility across our offices. Such mobility is, however, subject to business needs and regulations governing immigration and employment in various countries. Selection process: We seek to be transparent during the selection process. While the actual process may vary from the process indicated below, the key steps involved are as follows: - Interview: There are expected to be at least 3 rounds of interviews. The number of interview rounds may increase depending on the criticality and seniority of the role involved. - Final discussion on career and compensation: Post final selection, a separate discussion will be set up to discuss compensation and career growth. You are encouraged to seek any clarifications you have during this discussion. Preparation required: It is recommended that you prepare on the following aspects before the selection process: - Experience with AI/ML platforms, enterprise data platforms, or modern application architectures. - Cloud certifications (Azure Solutions Architect, AWS Solutions Architect, Kubernetes Administrator, etc.). - Experience selling or positioning managed services, professional services, or infrastructure offerings. - Experience working with large enterprise and regulated industry customers.