Job
Description
Job Description Role: AI Engineer Employment Type: Full-Time, Permanent Location: On-site, Bengaluru Vacancies: Multiple Positions Company Overview EmployAbility.AI is an AI-driven career enablement platform dedicated to transforming how individuals and organizations navigate the future of work. We are committed to democratizing access to meaningful employment by using advanced artificial intelligence, real-time labor market data, and intelligent career pathways to bridge the gap between skills and opportunities. Our platform empowers job seekers with personalized career insights, learning recommendations, and job-matching tools while enabling organizations to make smarter hiring and workforce development decisions. By aligning talent capabilities with market demand, we help create a more inclusive, adaptive, and future-ready workforce. At EmployAbility.AI, we’re not just building software—we’re building solutions that make employability equitable, data-driven, and scalable. Job Role: AI Engineer As an AI Engineer at EmployAbility.AI, you will be at the forefront of building intelligent systems that power the platform’s core functionality—from LLM-based recommendations to intelligent search and contextual assistants. You will develop and deploy state-of-the-art AI models and pipelines using LLMs , LangChain , and Retrieval-Augmented Generation (RAG) to deliver impactful, real-world solutions. You will work closely with a cross-functional team of developers, data scientists, and product managers to create scalable, production-ready AI features that enhance user experiences and drive measurable value across industries and regions. Key Responsibilities Design and develop AI-driven features including conversational agents, recommendation engines, and smart search using LLMs. Build and integrate LangChain-based applications that leverage RAG pipelines for improved reasoning and contextual understanding. Fine-tune, evaluate, and optimize transformer models (BERT, GPT, LLaMA, etc.) for domain-specific use cases. Work with unstructured and semi-structured data (e.g., resumes, job descriptions, labor market datasets). Develop embedding-based search using tools like FAISS , Pinecone , or Weaviate . Collaborate with backend and frontend teams to integrate AI services via scalable APIs. Perform data preprocessing, feature engineering, and model evaluation. Monitor performance of deployed models and iterate based on feedback and metrics. Participate in prompt engineering, experiment tracking, and continuous optimization of AI systems. Stay updated on the latest trends in AI/ML and contribute to internal knowledge sharing. Education Requirements B.Tech/B.E, M.Tech, MCA, M.Sc, MS, or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Core Technical Skills – AI Engineering Large Language Models & NLP Experience with LLMs and transformer-based architectures (e.g., GPT, BERT, LLaMA). Hands-on with LangChain framework and RAG (Retrieval-Augmented Generation) workflows. Proficiency in prompt engineering , embedding models, and semantic search. Experience using Hugging Face Transformers , OpenAI API , or open-source equivalents. Vector Stores & Knowledge Retrieval Experience with FAISS , Pinecone , or Weaviate for similarity search. Implementation of document chunking, embedding pipelines, and vector indexing. ML/AI Development Strong skills in Python and ML libraries (PyTorch, TensorFlow, Scikit-learn). Familiar with NLP tasks like named entity recognition, text classification, and summarization. Experience with API development and deploying AI models into production environments. Tooling & Development Practices Version control with Git , collaborative workflows via GitHub Experiment tracking with MLflow , Weights & Biases , or equivalent API testing tools (Postman, Swagger), and JSON schema validation Use of Jupyter notebooks for experimentation and prototyping Deployment & DevOps (Basic Understanding) Containerization using Docker , basic orchestration knowledge is a plus Cloud environments: familiarity with AWS , GCP , or Azure CI/CD workflows (GitHub Actions, Jenkins) Monitoring tools for model performance and error tracking (Sentry, Prometheus, etc.) Soft Skills & Work Habits Strong problem-solving and analytical thinking Ability to work cross-functionally with technical and non-technical teams Clear and concise communication of complex AI concepts Team collaboration and willingness to mentor peers or juniors Agile/Scrum practices using tools like Jira, Trello, and Confluence Bonus Skills (Good to Have) TypeScript or JavaScript for frontend or integration work Knowledge of GraphQL , chatbot development , or multi-modal AI Familiarity with AutoML , RLHF , or explainable AI Experience with knowledge graphs , ontologies , or custom taxonomies Show more Show less
