Cloud Platform Engineer

Description:

We are seeking a Generative AI Engineer with a strong technical background and hands-on experience in Python programming. This role requires expertise in developing, implementing, and optimizing Gen AI-driven solutions using cloud platforms, particularly AWS services such as Bedrock.

As a GenAI Engineer, you will be at the forefront of integrating cutting-edge AI capabilities into scalable and efficient solutions that meet evolving business needs. Your primary focus will be to develop, test, and refine AI-driven applications, ensuring they are robust, efficient, and aligned with industry best practices.

Key Responsibilities:

• Develop, test, and deploy Generative AI models using LangChain, AWS Bedrock, and other AI frameworks.

• Leverage Vector Databases (e.g., AlloyDB, Aurora PostgreSQL DB) to enhance AI search efficiency, knowledge retrieval, and retrieval-augmented generation (RAG) for improved contextual responses.

• Design effective prompts to optimize AI-generated outcomes through prompt engineering.

• Implement search and retrieval techniques, including code ingestion and knowledge retrieval to enhance AI performance.

• Debug AI models and cloud-based solutions independently, particularly within AWS environments.

• Build and integrate frontend applications using Streamlit and backend services using Python to create end-to-end AI applications.

• Collaborate with cross-functional teams to test AI-driven solutions, gather feedback, and enhance system capabilities.

• Communicate complex AI concepts effectively to non-technical stakeholders, ensuring clarity in AI adoption and implementation.

• Actively contribute to team discussions, providing insights and proposing solutions to AI-related challenges.

Top 3 Skills to have:

• Proficiency in Python – Strong programming skills, especially in AI/ML model development, API integration, and cloud-based deployment.

• Prompt Engineering Expertise – Ability to craft, test, and optimize AI prompts to improve LLM (Large Language Model) performance.

• Experience with Vector Databases (e.g. AlloyDB, Aurora PostgreSQL DB) – Knowledge of retrieval-augmented generation (RAG) techniques and efficient AI memory storage.

Top 3 Skills that are good to have:

• AWS Cloud Certification – Holding certifications such as AWS Certified Machine Learning or AWS Certified Solutions Architect demonstrates expertise in cloud-based AI deployment and optimization.

• Exposure to Multiple Programming Languages – Proficiency in languages beyond Python, such as Java, React, and Angular.

• Deep Awareness of Emerging AI Trends & Innovations – Ability to continuously research, evaluate, and apply the latest advancements in Generative AI and cloud-based AI solutions, ensuring the organization remains at the cutting edge of AI-driven transformation.