AI Platform Engineer

We are looking for a highly skilled AI Platform Engineer with 4-6 years of experience in building AI-driven applications using large language models (LLMs) and modern AI frameworks. The ideal candidate will have hands-on expertise in designing, developing, and deploying GenAI solutions such as chatbots, automation tools, intelligent assistants, and AI-powered workflows that solve real business problems. You will work closely with cross-functional teams to integrate AI capabilities into products and processes, ensuring scalable, secure, and production-ready implementations.

Responsibilities:

• Design, develop, and deploy applications powered by Large Language Models (LLMs).
• Build and optimise RAG (Retrieval Augmented Generation) pipelines using vector databases.
• Develop AI agents and automation workflows using modern agent frameworks.
• Fine-tune, evaluate, and optimise models for performance, accuracy, and cost efficiency.
• Integrate AI models with enterprise systems through APIs and microservices.
• Implement prompt engineering strategies and guardrails for safe AI usage.
• Work on multimodal AI applications (text, images, audio) when required.
• Deploy AI solutions on cloud platforms, ensuring scalability and reliability.
• Collaborate with product managers, data scientists, and engineers to deliver AI features.
• Stay updated with the latest advancements in generative AI technologies.

Requirements:

• Strong problem-solving mindset.
• Passion for emerging AI technologies.
• Ability to work in fast-paced environments.
• Ownership mindset with focus on delivery.
• Bachelor's or master's degree in technology in computer science, artificial intelligence, data science, engineering, or a related field.

Core Technical Skills:

• Strong programming experience in Python.
• Hands-on experience with LLM APIs (OpenAI, Azure OpenAI, Anthropic, Gemini, etc. ).
• Experience with LangChain, LlamaIndex, or similar orchestration frameworks.
• Knowledge of vector databases (Pinecone, Weaviate, FAISS, Chroma, and Milvus).
• Experience in building RAG-based applications.
• Understanding of Prompt Engineering and Model Evaluation Techniques.
• Experience with REST APIs, FastAPI, or Flask.
• Familiarity with Docker, Git, and CI/CD pipelines.

Cloud and Deployment:

• Experience with at least one cloud platform: AWS / Azure / GCP.
• Knowledge of Kubernetes (good to have).
• Knowledge of serverless deployment.
• Knowledge of model monitoring tools.

Preferred Skills (Good to Have):

• Experience building AI agents / autonomous systems.
• Knowledge of MLOps / LLMOps practices.
• Experience with speech-to-text / text-to-speech systems.
• Frontend integration knowledge (React / Streamlit / Next.js ).
• Experience working with enterprise data systems and databases (SQL / NoSQL).
• Understanding of AI safety, governance, and responsible AI principles.