About the Role :

We are seeking a highly capable and motivated PX-Gen AI Engineer with hands-on expertise in Python, Generative AI (Gen AI), Agentic AI, and ML systems development. The ideal candidate will be proficient in developing and deploying LLMs, building scalable APIs, and integrating cloud-native AI solutions on AWS and Azure platforms.

You'll be part of an advanced engineering team working on cutting-edge Gen AI systems, including agent-based architectures, model fine-tuning, LLM evaluation, and full-stack AI application delivery.

Key Responsibilities :

Model Fine-Tuning & Training :

- Fine-tune Large Language Models (LLMs) for specific business tasks using frameworks like PyTorch, Langchain, DSPy, etc.

- Improve model accuracy and efficiency through training optimization and data augmentation strategies.

Model Deployment & Integration :

- Deploy models in production using AWS or Azure, and containerize using Docker.

- Build cloud-native, scalable Gen AI services using offerings like Cognitive Services, API Management (APIM), App Services, and S3/Object Storage.

API Development & Web Integration :

- Build robust, RESTful APIs using FastAPI or Flask to serve ML models and LLMs.

- Integrate APIs with third-party systems and ensure secure, high-performance communication.

Agentic AI & LLM Evaluation :

- Develop and evaluate Agentic AI systems capable of decision-making, task orchestration, and dynamic workflow execution.

- Design testing and evaluation pipelines for LLMs to assess quality, coherence, latency, and use-case effectiveness.

Search & Indexing :

- Implement NLP-based search and indexing systems using tools like Elasticsearch, FAISS, or similar.

- Optimize information retrieval for semantic understanding and relevance scoring.

Research & Innovation :

- Stay abreast of the latest developments in Generative AI, NLP, LLM architectures, and multi-agent frameworks.

- Bring new ideas and innovations into existing platforms and solutions.

Mandatory Skills :

- Programming : Python (expert level)

- AI/ML Fundamentals : Strong foundation in ML algorithms and DL architectures

- Gen AI & LLMs : Langchain, LangGraph, PyTorch, DSPy

- Web Frameworks : FastAPI, Flask

- Cloud Platforms : AWS (primary), Azure (secondary)

- Agentic AI : Experience with multi-agent or autonomous system design

- DevOps Tools : Docker, API development, LLM evaluation pipelines

Skills to Evaluate (Technical Assessment) :

- Python

- Generative AI

- AWS (services for AI/ML)

- Agentic AI

- ML fundamentals

- Flask & FastAPI (API frameworks)

- PyTorch (model training/fine-tuning)

Preferred Skills :

- Exposure to search/indexing systems (e.g., FAISS, Pinecone, Elasticsearch)

- Understanding of LLMOps and Model-as-a-Service deployment practices

- Familiarity with SpaCy, MCP, and LangGraph

- Experience deploying LLMs at scale with GPU/TPU integration

Qualifications :

- Bachelor's or Master's in Computer Science, AI/ML, or a related engineering discipline

- 5-7 years of relevant experience in AI/ML engineering

- Proven track record in building Gen AI solutions for production use