Key Activities :

- Architect end-to-end AI/ML solutions tailored to business requirements, ensuring scalability and performance.

- Experienced in use case discovery, scoping, and delivering complex solution architecture designs to multiple audiences requiring an ability to context switch in levels of technical depth across AI/ML technologies and platforms.

- Architect production level AI agent/RAG solutions for customers using our unified platform, including end-to-end ML pipelines, inference optimization, integration with cloud-native services and MLOps

- Provide guidance and best practices to development teams on AI agent implementations.

- Serve as the trusted technical advisor for customers developing GenAI solutions, such as RAG architectures on enterprise knowledge repo and ensure high-quality, efficient, and maintainable code for AI agents.

- Oversee the ingestion, transformation, and validation of large datasets for model training and deployment using AA or 3rd party hyper scaler platform.

- Implement and manage CI/CD pipelines for seamless model deployment and monitoring in production.

- Track and improve the performance of AI/ML systems through testing, validation, and iterative improvements.

- Stay updated on advancements in AI/ML and identify opportunities for integrating new techniques into solutions.

- Work closely with product managers, data scientists, and engineering teams to align on technical goals and deliverables.

- Create detailed architectural diagrams, technical documentation, and best practice guidelines.

- Address critical production issues and optimize system reliability and performance.

- Mentor team members and contribute to organizational learning in AI/ML technologies.

Skills & Qualifications Criteria :

Must Have Skills :

- 7 to 10 yrs of overall IT experience with 5+ years of experience in AI/ML implementations

- Deep knowledge of machine learning, deep learning, and natural language processing algorithms and frameworks (TensorFlow, PyTorch, Hugging Face, etc.).

- Experience with the latest techniques in natural language processing including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI

- Hands-on experience with AI/ML services on AWS, GCP, or Microsoft Azure. Have completed certifications from either of these hyper scaler providers.

- Strong programming skills in Python, Java, or other relevant languages;

- Familiarity with RAG (Retrieval-Augmented Generation) methodologies and integrating Generative AI into enterprise applications.

- Hands-on expertise in prompt engineering, RAG, vector DBs and technologies to implement AI agent solutions.

- Expertise in data preprocessing, feature engineering, and working with large-scale data pipelines (Apache Spark, Kafka, etc.).

Nice to have skills :

- Strong background on cloud services from various cloud service providers that integrates with AI/ML solutions

- Experience with MLOps tools like MLflow, Kubeflow, or SageMaker.

- Proficiency in deploying, monitoring, and optimizing models in production environments.

- Ability to design scalable, secure, and high-performance AI/ML solutions.

- Strong analytical skills to address complex technical challenges and innovate scalable solutions.

- Ability to articulate technical concepts to diverse audiences, including non-technical stakeholders.

- Experience mentoring engineers and collaborating with cross-functional teams.

- Understanding of data privacy and AI ethics for compliant system designs.