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 architecturesGen AI & LLMs : Langchain, LangGraph, PyTorch, DSPyWeb Frameworks : FastAPI, FlaskCloud Platforms : AWS (primary), Azure (secondary)Agentic AI : Experience with multi-agent or autonomous system designDevOps Tools : Docker, API development, LLM evaluation pipelinesSkills to Evaluate (Technical Assessment) :
PythonGenerative AIAWS (services for AI / ML)Agentic AIML fundamentalsFlask & 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 practicesFamiliarity with SpaCy, MCP, and LangGraphExperience deploying LLMs at scale with GPU / TPU integrationQualifications :
Bachelor's or Master's in Computer Science, AI / ML, or a related engineering discipline5-7 years of relevant experience in AI / ML engineeringProven track record in building Gen AI solutions for production use(ref : hirist.tech)
