Salesforce Architect Manager

Salesforce · India - Hyderabad · India - Bangalore · India - Pune · India - Gurgaon

hybridfull-time6-10 years

posted 4 Aug

Skills: Salesforce, CRM

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Customer Success Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. We are seeking a Technical Architect & Salesforce Manager to join our consulting team. In this hybrid role, you will act as a billable Technical Architect on active client engagements—designing robust, scalable Salesforce solutions—while simultaneously managing and mentoring a team of skilled Salesforce Developers to ensure technical excellence, professional growth, and successful project delivery. You are both a big picture thinker and in-depth problem solver, your knowledge and skills are both broad and deep. You take pride in designing systems that stand up to high volumes and won't fail at critical points. You have a good mix of technical and enterprise skills from a technology perspective, including a foundational understanding of how to leverage AI development tools to optimize delivery cycles. The solutions you design are built for the long-term and will scale with the customer's growth plans seamlessly. You have proven experience integrating systems via API’s as well as a strong development background. You are able to lead and motivate a team of highly capable individuals and help them meet their targets while enabling their growth. Responsibilities and Requirements: Collaborate with client stakeholders to define requirements, deliverables, and set and manage expectations Drive Enterprise AI Architecture by designing and integrating scalable predictive and generative AI solutions within custom Salesforce environments, optimizing performance, resource consumption, and platform governor limits Lead technical design sessions; architect and document technical solutions aligned with client business objectives; identify gaps between client's current and desired end states, using advanced LLMs like Claude to review architectural assumptions and simulate system edge cases Champion an AI-first delivery methodology, utilizing advanced AI tools, developer assistants (e.g., Cursor, Claude), and agentic evaluation frameworks to accelerate implementation across projects Provide oversight and governance of Salesforce projects, guiding delivery teams on the effective use of AI-assisted tooling to maintain velocity and quality Follow and help define coding standards. Lead code reviews during projects to ensure quality and appropriate design patterns are followed, encouraging the use of AI coding assistants to enforce best practices Manage the technical delivery of custom development, integrations, and data migration elements of a Salesforce implementation Ability to understand a project and debug issues, leveraging AI diagnostics to assist in interpreting logs and isolating bottlenecks From time-to-time, participate in activities such as technical landscape discovery, Proof-Of-Concept (POC) development with prospects Liaise with Salesforce product teams to support client implementations Expert level understanding of the Salesforce product suite, including Sales, Service, Community, Marketing, and Commerce Clouds, with a foundational familiarity with Salesforce's AI offerings (e.g., Agentforce) Understanding of systems architecture Understanding of key design patterns and large data volume limitations and best practices Understandin