Designation: Gen AI Engineer
Experience: 3 - 5 Years
Location: Ahmedabad
Priority: Immediate joiners preferred

Job Summary:
We are seeking an Gen AI Engineer with 3+ years of experience in building and deploying intelligent systems. The role focuses on developing scalable ML solutions, optimizing models, and solving real-world business problems.

Key Responsibilities:

- Design, develop, train, evaluate, and deploy ML/DL models
- Work on classification, regression, clustering, NLP, and recommendation systems
- Perform data preprocessing, feature engineering, hyperparameter tuning, and model optimization
- Hands-on experience with AI tools and developer productivity tools such as n8n, Cursor, Claude, ChatGPT, GitHub Copilot, and similar AI-assisted automation/coding platforms
- Experience using AI tools effectively for automation, development workflows, debugging, code generation, and productivity enhancement
- Build and fine-tune Generative AI models (LLMs, VAEs, diffusion models) using Hugging Face, LangChain, OpenAI, LlamaIndex
- Develop RAG pipelines, prompt engineering workflows, and embedding-based search systems
- Build Multi-Agent Systems and agent workflows using CrewAI, LangGraph, AutoGen, etc.
- Integrate AI solutions into scalable production systems
- Monitor model performance, accuracy, latency, and reliability
- Collaborate with cross-functional teams and stay updated with latest AI/ML advancements

Requirements:

- Strong Python programming skills
- Strong understanding of ML concepts:
- Hands-on experience with TensorFlow, PyTorch, Scikit-learn, or Keras
- Practical experience in:
- Model training & fine-tuning
- LLMs & Generative AI
- RAG architecture
- Prompt Engineering
- Embeddings & Vector Search

- Experience with vector DBs: Pinecone, Weaviate, Chroma, FAISS
- Experience with LangChain, LlamaIndex, OpenAI APIs




- Knowledge of Multi-Agent/Agentic AI systems
- Experience with FastAPI/Flask model deployment
- Familiarity with AWS/GCP/Azure
- Knowledge of Git and MLOps tools (MLflow, Airflow, Kubeflow)
- Basic understanding of Spark/Hadoop and ETL pipelines

What we offer:

- 5-day work week & Versatile work hours
- Growth-focused journey with regular rewards and recognition
- Focus on learning & development
- Competitive, goal-driven culture

Skills Building and deploying intelligent systems, Developing scalable ML solutions, Optimizing models, Solving real-world business problems, Design ML/DL models, Train ML/DL models, Evaluate ML/DL models, Deploy ML/DL models, Classification, Regression, Clustering, NLP, Recommendation systems, Data preprocessing, Feature engineering, Hyperparameter tuning, Model optimization, AI tools, Developer productivity tools, n8n, Cursor, Claude, ChatGPT, GitHub Copilot, AI-assisted automation, AI-assisted coding, Automation, Development workflows, Debugging, Code generation, Productivity enhancement, Build Generative AI models, Fine-tune Generative AI models, LLMs, VAEs, Diffusion models, Hugging Face, LangChain, OpenAI, LlamaIndex, Develop RAG pipelines, Prompt engineering workflows, Embedding-based search systems, Build Multi-Agent Systems, Agent workflows, CrewAI, LangGraph, AutoGen, Integrate AI solutions, Scalable production systems, Monitor model performance, Model accuracy, Model latency, Model reliability, Cross-functional collaboration, Python, TensorFlow, PyTorch, Scikit-learn, Keras, Model training, Fine-tuning, LLMs, Generative AI, RAG architecture, Prompt Engineering, Embeddings, Vector Search, Vector DBs, Pinecone, Weaviate, Chroma, FAISS, LangChain, LlamaIndex, OpenAI APIs, Multi-Agent AI systems, Agentic AI systems, FastAPI, Flask, Model deployment, AWS, GCP, Azure, Git, MLOps tools, MLflow, Airflow, Kubeflow, Spark, Hadoop, ETL pipelines

📌 Gen AI Engineer (Ahmedabad)
🏢 Techify Solutions
📍 Ahmedabad