The ideal candidate will have a solid foundation in software engineering, AI/ML technologies, and software development processes. The Candidate will be responsible for guiding a team of 4-5 AI developers, ensuring the delivery of robust AI solutions while maintaining high standards in architecture, coding practices, and project execution.

Required AI/ML Skills :

Generative AI (GenAI) :

- Experience with Large Language Models (LLMs) like GPT, BERT, or LLaMA.

- Familiarity with fine-tuning LLMs and integrating them into enterprise applications and Databases.

- Knowledge of text generation, summarization, translation, and conversational AI.

Traditional Machine Learning :

- Proficiency in ML techniques like supervised learning, unsupervised learning, and reinforcement learning.

- Hands-on experience with classification, regression, clustering, and time-series forecasting.

AI Frameworks and Tools :

- Proficient in frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn, and Keras.

- Familiarity with ML pipelines using tools like MLflow, Kubeflow, or TensorFlow Extended (TFX).

Deployment :

- Knowledge of containerization (Docker, Kubernetes) and serverless architectures for scalable AI solutions.

Required Software Engineering Skills :

Programming Languages :

- Strong proficiency in Python (preferred), Java, or Go for AI application development.

- Experience with API development frameworks such as FastAPI, Django, or Flask.

Architectural Concepts :

- Deep understanding of microservices architecture, event-driven design, and RESTful APIs.

- Knowledge of distributed systems and high-performance computing.

Soft Skills :

Communication and Presentation :

- Excellent verbal and written communication skills, with the ability to simplify complex technical concepts for diverse audiences.

- Strong presentation skills to effectively convey architectural designs and project updates to customers and stakeholders.

Team Collaboration :

- Proven experience in leading and mentoring technical teams, fostering collaboration, and encouraging continuous learning.

- Ability to work effectively across cross-functional teams including data engineers, product managers, and QA engineers.

Key Responsibilities :

Technical Leadership :

- Lead, mentor, and guide a team of AI developers.

- Ensure adherence to best practices in software engineering, AI model development, and deployment.

- Review and approve architectural designs, ensuring scalability, performance, and security.

AI Application Development :

- Architect and design AI solutions that integrate both Generative AI (GenAI) and traditional Machine Learning (ML) models.

- Oversee the end-to-end development lifecycle of AI applications, from problem definition to deployment and maintenance.

- Optimize model performance, ensure model explainability, and address model drift issues.

Architectural Oversight :

- Develop and present the big-picture architecture of AI applications, including data flow, model integration, and user interaction.

- Dive deep into individual components, such as data ingestion, feature engineering, model training, and API development.

- Ensure the AI solutions align with enterprise architectural standards and customer requirements.

Customer Engagement :

- Act as the primary technical interface for customer meetings, providing clear explanations of the AI solutions architecture, design decisions, and project progress.

- Collaborate with stakeholders to understand business needs and translate them into technical requirements.

- Ensure proper documentation, including design documents, code reviews, and testing protocols.

- Monitor project timelines and deliverables, ensuring high-quality outcomes.

Qualifications :

- Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or related field.

- 6-9 years of experience in developing and deploying AI applications.

- Proven track record of delivering scalable AI solutions in an enterprise setting.