Location: Hyderabad
Job Type: full Time
Salary: 100,000 – 120,000
Your New Role:
As the Manager – AI Application Development, you will play a pivotal role in designing, building, and deploying AI-powered applications that drive innovation and efficiency across Warner Bros. Discovery. This role requires a balance of technical expertise, leadership, and collaboration to deliver scalable, production-grade AI solutions that align with enterprise transformation goals.
You will lead a team of AI engineers and developers, collaborating with cross-functional stakeholders to translate business challenges into impactful AI applications. Working in one of the world’s largest Media & Entertainment companies, you will be at the forefront of building intelligent systems that enhance decision-making, optimize operations, and unlock new business opportunities.
Your responsibilities include driving the adoption of automation platforms (such as RPA, IPA, and cloud-based tools), integrating Agentic AI for adaptive and context-aware workflow automation, and ensuring solutions are robust, compliant, and measurable. This is a unique opportunity to influence the company’s automation strategy and champion the next wave of AI-enabled enterprise productivity.
1. AI Application Development & Delivery
- Lead the design, development, and deployment of AI/ML applications that solve high-impact business problems.
- Translate business requirements into technical solutions leveraging advanced AI/ML techniques.
- Ensure AI models are integrated into user-friendly applications with robust APIs, dashboards, and enterprise systems.
- Drive best practices in software engineering, MLOps, and scalable cloud deployment.
2. Team Leadership & Mentoring
- Manage a team of AI engineers and developers, setting goals, guiding technical execution, and fostering growth.
- Mentor junior team members, promoting excellence in AI coding practices, model deployment, and system design.
- Ensure the team delivers high-quality, production-ready AI applications on time.
3. Architecture & Technology Strategy
- Define architecture standards for AI application development and integration with enterprise platforms.
- Ensure applications are scalable, secure, and compliant with industry regulations.
- Stay ahead of emerging AI technologies (GenAI, Agentic AI, LLMOps) and assess their applicability for enterprise adoption.
4. Stakeholder Engagement & Collaboration
- Partner with product managers, data scientists, business teams, and senior leaders to align solutions with strategic priorities.
- Clearly communicate complex AI concepts and application value to both technical and non-technical stakeholders.
- Build strong relationships with vendors, cloud providers, and external partners to accelerate innovation.
5. Governance, Risk & Continuous Improvement
- Implement best practices for governance, risk management, and compliance in AI application delivery.
- Monitor and optimize application performance to ensure scalability and reliability.
- Continuously enhance development practices to improve speed, quality, and maintainability of AI solutions.
Qualifications & Experiences:
Academic Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
- Certifications in AI/ML, Cloud (AWS/Azure/GCP), or application development frameworks are desirable.
Professional Experience:
- 8–10 years of professional experience in AI/ML, software engineering, or application development.
- Proven track record of building and deploying AI-powered applications at scale in enterprise environments.
- Strong experience with Python, Java/JavaScript, or similar programming languages for AI integration.
- Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and cloud AI platforms (AWS SageMaker, Azure AI, Bedrock, etc.).
- Exposure to GenAI/LLM-based applications, prompt engineering, and API-based deployments is highly desirable.
- At least 3+ years of leadership/managerial experience managing teams of developers/engineers.
Technical Skills:
- Strong proficiency in Python and ML pipeline development.
- Experience with MLOps tools (MLflow, Kubeflow, Airflow) and CI/CD for AI.
- Familiarity with microservices, REST APIs, and containerization (Docker, Kubernetes).
- Good understanding of software engineering practices (Agile, DevOps, SDLC).
- Knowledge of data engineering and integration with enterprise data lakes/warehouses.
Other Skills:
- Excellent leadership, team-building, and interpersonal skills with the ability to engage stakeholders at all levels.
- Strong project management skills, with experience in overseeing end-to-end automation projects, ensuring timely and on-budget delivery.
- Exceptional communication skills, both written and verbal, with the ability to articulate complex automation strategies to non-technical audiences.
- Strong analytical and problem-solving skills with a focus on process optimization and continuous improvement.
- A proactive, self-motivated approach to identifying opportunities for automation and driving their implementation.