Practice Manager - Cloud, DevOps & AI Practice

Job Description

Practice Manager – Cloud, DevOps & AI Practice Company: Teceze Ltd Position: Practice Manager – Digital Engineering & AI Innovation Practice Area: Cloud & DevOps, AI & Intelligent Automation, Application Modernization Location: Chennai or Bangalore Employment Type: Full-time About Teceze Teceze is a global technology partner focused on operational resilience, digital transformation, and scalable growth. We simplify architectural complexity and accelerate business velocity by uniting next-generation innovation under a highly accountable delivery model. Our Digital Engineering Innovation Engine integrates Cloud & DevOps frameworks, Application Modernization, and AI & Intelligent Automation . We construct production-grade computing, delivery pipelines, and data architectures that allow enterprise clients to transform legacy operational structures into scalable, future-ready business outcomes. Position Overview We are seeking a visionary, growth-oriented, and highly execution-driven Practice Manager to lead and scale our Cloud, DevOps, and AI Practice . In this strategic role, you will hold end-to-end accountability for the health, growth, capabilities, and delivery excellence of this specialized business unit. You will operate at the intersection of business strategy, technology leadership, and talent enablement. As the Practice Manager, you will define our market offerings, support pre-sales engineering to win high-impact enterprise accounts, oversee global delivery frameworks, and cultivate a world-class engineering team. The ideal candidate can confidently pivot between high-level C-suite consulting and deep technical governance across public cloud, continuous integration, and generative AI initiatives. Key Responsibilities 1. Practice Strategy & Offering Development Define the commercial roadmap, solution offerings, and go-to-market (GTM) strategy for the Cloud, DevOps, and AI practice lines. Continuously evaluate emerging tech trends (e.g., LLMOps, serverless architectures, FinOps, agentic AI workflows) to build highly relevant, repeatable transformation playbooks for enterprise clients. 2. Pre-Sales Support & Revenue Acceleration Partner closely with the Business Development team as the primary technical and strategic authority during early-stage client pursuits. Lead executive discovery workshops, architect high-level solutions, review technical proposals, and construct robust Statements of Work (SOWs). Drive practice-sourced revenue growth by identifying expansion opportunities within existing accounts. 3. Delivery Governance & Quality Assurance Provide leadership, technical direction, and delivery oversight across a portfolio of complex digital transformation projects. Ensure projects are executed on time, within scope, and aligned with enterprise architectural best practices (e.g., Well-Architected Frameworks). Act as the ultimate escalation point for delivery hurdles, working alongside Solution Architects to maintain client satisfaction. 4. Talent Management & Capability Building Attract, mentor, and retain a high-performing team of cloud engineers, DevOps professionals, and AI/Data scientists. Establish structured training programs, clear certification pathways (AWS, Azure, GCP, NVIDIA, Hugging Face), and standard engineering methodologies to keep the practice at the absolute cutting edge. Requirements & Qualifications Experience 10 to 14+ years of total IT experience, with at least 3 to 5 years spent in a practice leadership, delivery management, or principal consulting role within a global systems integrator or managed IT services environment. A proven track record of managing a technical business unit, including direct experience driving pre-sales pipelines and hitting utilization/profitability benchmarks. Demonstrated experience successfully steering multi-cloud transformations, agile software delivery initiatives, and enterprise AI production deployments out of sandbox environments. Technical Fluency Cloud & DevOps: Strong conceptual and strategic understanding of multi-cloud architectures (AWS, Azure, GCP), Infrastructure as Code (Terraform), container orchestration (Kubernetes), and modern CI/CD patterns. Artificial Intelligence: solid understanding of Machine Learning lifecycles (MLOps), Generative AI deployment architectures (RAG systems, vector data engineering), and data integration pipelines. Ability to evaluate the commercial feasibility, infrastructure costs, and business ROI of complex technical systems. Core Competencies Executive Presence: Superb communication, negotiation, and storytelling skills, with comfort acting as a trusted advisor to C-level executives (CIOs, CTOs, CDOs). Operational Excellence: Strong organizational skills with the ability to manage resource allocation, project utilization rates, and global delivery margins effectively.