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.
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