Head of Practice, Data and AI

Head of Practice, Data and AI

Job Description

Job Description Multi-Market engineering unit of BGSW provides services to Bosch consumer goods, industry, healthcare and energy business units and Global customers.

Multi-Market unit hosts robust engineering capabilities and strong technology horizontals like Data and AI, Applications lifecycle and Value streams solutions.

The Data and AI Practice within BGSW comprises of distinctive sub-practices with Global P&L responsibilities : AI / ML Services and software Platform development on MLOps, Responsible AI and their GTM forays for Bosch Group and Its customers.Be the delivery units for GenAI program house for GenAI based Engg Efficiency, Customer experience and Engg design topics across Multi Market Engineering UnitsAI / ML offerings to Global Clientele in Service-Delivery model ( in the areas of AI / ML, GenAI, MLOps, Responsible AI, Gen AI for Engg, Hyper Automation , Conversational AI and Agentic AI )Data Engineering 'font-size : 10.0pt;font-family : Arial'>

offerings to Bosch and Global Clientele in Service-Delivery modelBring in Innovative end-to-end business solutions using advanced Data Science techniques, to unlock previously unknown, but meaningful, business relationships allowing clients to significantly improve profitability through more informed insights.

Job Description Key responsibilities : People Leadership : Lead and manage a team and support their professional development. Foster a collaborative and productive team environment. Managing team targets and goals in line with a practice plan. Technical Leadership : Provide guidance and leadership in the development of embedded software and validation projects.Mentor team, providing support and knowledge transfer to enhance team capabilities.Stay updated on industry trends, emerging technologies, and best practices in embedded systems design.Enhance efficiency and productivity by implementing and improving engineering processes, workflows, and methodologies. Delivery Management : Manage the project lifecycle to ensure timely, high-quality deliverables.Ensuring projects are adequately staffed and deliver high-quality work.Ensure the delivery of high-quality services that meet customer expectations and project

requirements.Implement quality assurance processes, conduct regular reviews, and address any quality issues or deviations. Thought Leadership : Develop and oversee the technical roadmap for the practice area, ensuring alignment with overall business goals.Drive innovation by identifying and developing assets, solutions and IP's that align with organization's needs.Remain at the forefront of innovation by staying updated on industry advancements. QualificationsBachelors / Master's degree in Engineering, preferably with an MBA18+ years' experience in leading Engineering IT teamsStrong delivery management experience with PMP certificationExperience working in complex, ambiguous environments with cross-functional teamsProven experience in productionizing AI / ML / NLP / CV projectsWillingness to keep up to date with latest industry tech trends on AI / ML and other niche technologies. Research mindset to understand upcoming trends and technologies and challenge the status quo.Providing thought leadership to develop and productionalize new operating model for the services of AI / ML, GenAI, MLOps, Responsible AI, Hyper Automation and Conversational AI .Possess strong interpersonal, com Qualifications

Educational qualification : Bachelors / Master's degree in Engineering, preferably with an MBA

Experience : 18+ years Mandatory / requires Skills : Program Management,Project cost management,Product Life Cycle Management,Project Risk Management,Project Portfolio Management,Requirement Management,Resource Management,Risk Management,Task Force Management

Qualifications

BE,Mtech degree in Engineering, preferably with an MBA

Additional Information

18+ years' experience in leading Engineering IT teams

Skills Required

data engineering , Project Portfolio Management, Resource Management, Program Management, Risk Management, MLops, Requirement Management, Project Risk Management, Product Life Cycle Management, task force management