AI Engineering Manager

Description :

Job Title : AI Engineering Manager

Location : Mumbai

About the Role :

We are looking for an experienced AI Engineering Manager with strong hands-on expertise in Java .The ideal candidate will drive the design, development, and deployment of scalable AI solutions while mentoring engineers, shaping technical strategy, and ensuring high-quality delivery across projects.

Key Responsibilities :

Technical Leadership :

- Lead the end-to-end development of AI/ML systems, platforms, and microservices.

- Architect scalable, high-performance solutions using Java, Spring Boot, and distributed systems.

- Guide the team on model integration, model serving, APIs, and ML-enabled features.

- Work closely with Data Science teams to convert ML models into production-grade applications.

- Oversee code quality, technical reviews, architecture decisions, and engineering best practices.

AI/ML Engineering :

- Manage the full lifecycle of ML models development, deployment, monitoring, and optimization.

- Build robust pipelines for data ingestion, model training, and model serving.

- Collaborate with Data Engineers to ensure clean, optimized, and reliable data flows for AI systems.

- Implement MLOps best practices (CI/CD, feature stores, model versioning, monitoring).

Team & People Management :

- Lead, mentor, and grow a team of AI/ML engineers and backend developers.

- Conduct 1 : 1s, performance reviews, and skill-development planning.

- Foster a culture of innovation, ownership, and continuous learning.

Cross-Functional Collaboration :

- Partner with Product Managers to translate business requirements into AI-powered features.

- Work with Cloud, DevOps, and Security teams to ensure high availability, reliability, and compliance.

- Coordinate with stakeholders to deliver projects on time and within scope.

Required Skills & Experience :

- 7-12 years of total experience, with at least 3+ years in managing engineering teams.

- Strong professional experience in Java, multithreading, system design, and scalable backend architectures.

- Hands-on experience with AI/ML engineering, model deployment, APIs, and ML-powered products.

- Good understanding of ML frameworks (TensorFlow, PyTorch), and ML pipelines.

- Experience with cloud platforms (AWS/Azure/GCP) and containerized environments (Docker, Kubernetes).

- Familiarity with MLOps tools : MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, etc.

Preferred Qualifications :

- Experience working in product-led tech or AI-driven organizations.

- Exposure to generative AI frameworks, LLM ops, vector databases, and prompt engineering.

- Knowledge of distributed computing, microservices architecture, and event-driven systems.

- Master's degree in Computer Science, Engineering, or related field is an advantage.

What We Offer :

- Opportunity to build and lead next-generation AI products.

- High ownership and autonomy in technical decision-making.

- Collaborative, innovation-driven culture.