
Generative AI Engineer
2 days ago
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 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
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