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.