Enterprise AI Engineering Director

InMobi Group's mission is to power intelligent, mobile-first experiences for enterprises and consumers. Its businesses across advertising, marketing, data and content platforms are shaping consumer experience in a world of connected devices. InMobians are passionate and driven, creative and fun-loving, take ownership and are outcome-driven. About AI Engineering Director - Enterprise

Digital & AI transformation across Inmobi is underway for - unlocking productivity & realizing efficiencies across the business, streamlining critical process flows and integrating cross-system architecture to achieve a lean and agile organizational set up.

This involves a strong understanding of the company's underlying business, system and process challenges, translating them into long term sustainable solutions that are applicable across InMobi's expanding business units. This team works across a spectrum of enterprise systems and products building end-to-end features and capabilities that help establish a fully integrated blueprint of the company's data architecture and system landscape. The Enterprise systems span the end-to-end value chain covering Lead generation, Sales & CRM, Order fulfilment, Service, Financial systems, BI Dashboards and NLP based Analytics.

Reporting to the Chief Digital Officer , this person will lead a team of engineers and collaborate deeply with Product managers, Designers and other Engineering teams, to build AI solutions grounded in consistent architectures and incorporates ongoing advancements. These AI solutions will help in Sales & Marketing transformation, Finance transformation, Service & Operational processes transformation.

Are you interested in shaping the era of AI, especially in an Enterprise context and scale? This role requires curiosity to understand the quickly growing AI landscape, continuous disruptive changes, knowledge in modern coding languages, different platforms (esp GCP/ Azure/ Salesforce), Machine Learning and LLMs.

As the Enterprise AI Engineering Leader, you are the face of the Enterprise AI engineering team, representing their work, and unblocking the team when problems arise. You manage a highly skilled team and help in the growth of their careers. You bring a deep understanding and expertise in digital transformation opportunities across AI, supported by thought leadership in technologies such as Generative AI, Advanced Analytics and App Modernization.

Lead the development, deployment, and optimization of AI (GenAI) Solutions, Tools, frameworks in the Enterprise space for core business process areas.

In this role, you will work closely with cross-functional teams, bringing technical expertise and hands-on problem-solving to ensure the successful delivery of AI solutions that support our business objectives (in the broad process areas described earlier)

Support POCs/ Pilots projects to explore and validate the ever-evolving AI technologies and solutions.

Stay updated regarding LLMs, MCP, A2A, ADK, Agentic AI landscape and the fast- changing AI technology & solution landscape - ensuring the innovations drive impact.

Participating in the full AI development lifecycle, including data preparation, design, coding, testing, deployment, and support.

Continuously assess and optimize software architecture, focusing on scalability, reliability, and alignment with emerging trends.

Mentor and enable career growth for your team.

Support upskilling and re-skilling of other Engineering team members + business users.

Supporting the development/ adoption/ optimization of AI-driven applications to meet organizational needs.

Proactively identifying and implementing automation/ AI capabilities – in an Enterprise setup.

Leveraging expertise in (Gen) AI solutions, Technologies & frameworks as listed above and enabling underlying system Integrations/ Infrastructure to deliver impactful solutions.

Excellent documentation and presentation skills for technical and non-technical audiences.

A bachelor's degree in Computer Science, Engineering, or a related field. Advanced degrees in AI and Data Science are a plus.

~ years of professional experience in Engineering/ Software development with increasing responsibility.

~ At least 4 – 5 years proven experience in implementing AI-driven applications.

~ Experience in developing and deploying machine learning models and AI solutions. Statistics and Probability Theory, Regression Modelling, Clustering Methods, Deep Learning, Neural Networks, Natural Language Processing, Text Mining, Computer Vision, Image Recognition, Time Series Forecasting, Machine Learning Visualization Tools, Tree Ensembles

~ Proficiency in programming languages like Python, R, or Java. Familiarity with AI and machine learning frameworks (e.Experience on big data technologies and tools (e.At least 2 years in Gen AI/ LLM based solutions. GCP/ Azure/ Salesforce / other platforms - Data and AI services, Data Engineering, Analytics, Machine Learning, Cognitive Services; Previous experience building a user-facing (Gen)AI/ LLM software applications

~ Strong technical proficiency in both frontend and backend development (e.React, Python, Java, Typescript).

~ Experience with design engineering, customer workshops, defining clear problem statements.

~ Demonstrated ability to work with complex datasets and perform data preprocessing and analysis.

Experience with code repositories including but not limited: Azure DevOps; understanding of Continuous Integration/Continuous Deployment (CI/CD) pipelines.

Experience with cloud technologies and infrastructure as code (e.AWS, Kubernetes, Terraform).

Familiarity with software design patterns, architecture trade-offs, and integration best practices.

Knowledge of DevOps practices, CI/CD pipelines, and automated testing frameworks.

Experience with database management and data processing.

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