Gen AI Engineer
Techify Solutions Pvt Ltd
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
- 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
- 5-day work week & Flexible work hours
- Growth-focused journey with regular rewards and recognition
- Focus on learning & development
- Competitive, goal-driven culture