Role - AI Engineer SA

Responsibilities
Designing, training, and deploying machine learning models and Large Language Models (LLMs) into production settings.
Collaborating in cross-functional engineering environments including front-end (React, Next.js) and platform team
Developing scalable, cloud-native microservices using tools like Docker and Kubernetes.
Building end-to-end AI applications integrated into web, mobile, or API-first platforms.
Managing CI/CD pipelines and observability for AI systems using tools such as GitHub Actions and MLflow.
Implementing vector databases, Retrieval-Augmented Generation (RAG) pipelines, and orchestration tools like LangChain and LlamaIndex.
Building and integrating multi-agent frameworks (e.g., LangGraph, LangFlow) to enable autonomous AI task execution.
Translating complex business problems into software-engineered AI solutions aligned with best practices.
Deploying on cloud platforms (AWS, GCP, Azure) and leveraging services such as SageMaker, Vertex AI, or Databricks.
Proficiency in Python and ML frameworks like PyTorch, TensorFlow, and Hugging Face Transformers.
Familiarity with LLM providers (OpenAI, Anthropic, Meta, etc.) and working with chat/image-based model outputs.




Hands-on experience with agent-based frameworks for intelligent orchestration.

Preferred Knowledge/Skills:

Building production web applications (solid internships or portfolio projects count)
Proficiency in Python and JavaScript/TypeScript, with hands-on experience in React
Familiarity with FastAPI, Flask, or a similar framework, and a solid understanding of REST APIs
Basic understanding of LLMs and prompting, and exposure to at least one agentic/LLM framework (LangChain, etc.) or a solid willingness to learn
Comfortable with Git, basic SQL, and writing tests

Additional experience or qualifications considered a plus:
Delivering AI applications using RAG, vector databases, and agent-based frameworks.
Working with multimodal inputs/outputs (text, image, audio).
Fine-tuning models on domain-specific data.
Applying Responsible AI practices including governance, bias mitigation, and ethics.
Ensuring consistency and quality in model outputs in production or regulated environments.
Contributing to open-source projects or AI/ML publications.
Full-stack development experience across front-end, back-end, and database layers.

📌 Artificial Intelligence Engineer Senior Associate Hyderabad
🏢 PwC
📍 Hyderabad