Role - AI Engineer SA

Responsibilities

- Designing, training, and deploying machine learning models and Large Language Models (LLMs) into production environments.

- 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 (strong 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