Job Summary :We are seeking an experienced AI Engineer with hands-on expertise in building LLM-powered applications and agentic workflows using models such as GPT, Claude, Llama, and other frontier models. The ideal candidate will have experience fine-tuning LLMs, using LangChain/LangGraph for multi-step agents, implementing function-calling, developing robust Python applications, and building scalable systems on GCP. Experience in RAG architectures, data science, and production-grade AI systems is essential.Key Responsibilities :1. Develop and Deploy AI Applications :- Design, develop, and deploy AI-driven applications utilizing large language models like GPT, Llama, and Claude.- Implement and optimize algorithms for natural language processing (NLP) tasks and other AI-related functionalities.- Create autonomous and semi-autonomous agents capable of planning, tool-use, and multi-step decision flows.2. Utilize LangChain/LangGraph :- Integrate LangChain and LangGraph to build robust agent workflows, tool orchestration, and memory-backed systems.- Implement advanced capabilities like routing, evaluation loops, and agent monitoring.3. Function Calling and API Integration :- Develop and maintain function-calling mechanisms for seamless integration with other services and applications.- Create and manage APIs to facilitate communication between AI models and external systems.4. Python Development :- Write clean, efficient, and scalable code in Python for AI and machine learning applications.- Use modern Python libraries (Pydantic, async frameworks, orchestration tools) to build reliable systems.5. GCP Cloud Services :- Deploy and manage AI and machine learning applications on Google Cloud Platform (GCP) infrastructure.- Utilize GCP services such as Compute Engine, Cloud Storage, Cloud Functions, and Vertex AI for model training, deployment, and storage.6.



Data Science and Machine Learning :- Apply core ML and data science methods to improve model performance and system reliability.- Build and maintain large-scale scraping and ingestion pipelines using Playwright, BeautifulSoup, etc.7. Retrieval-Augmented Generation (RAG) Systems :- Architect, optimize, and maintain RAG pipelines combining vector stores, embeddings, and hybrid search.- Improve retrieval quality, latency, filtering, and contextual relevance.8. Agentic Systems :- Build multi-tool, multi-step agent workflows capable of autonomous reasoning, planning, and execution.- Improve agent reliability through evaluation, guardrails, and structured output enforcement.9. Collaboration and Communication :- Collaborate with cross-functional teams to understand requirements and deliver AI solutions.- Communicate technical concepts and project progress to stakeholders effectively.Qualifications :- Bachelors/Masters degree in CS, Engineering, Data Science, or related fields.- 3 - 7 years of experience in AI/ML, with robust exposure to LLMs and agent frameworks.- Strong Python skills; experience with LangChain, LangGraph, Pydantic, and async tooling.- Hands-on GCP experience, including deploying production AI workloads.- Understanding of ML fundamentals, embeddings, vector databases, and retrieval systems.- Experience with function calling, API integrations, and RAG pipelines.- Strong problem-solving skills and attention to detail.- Ability to work independently and in collaborative environments.Preferred Skills :- Familiarity with multi-modal models and fine-tuning methods (LoRA, adapters).- Knowledge of MLOps and model monitoring practices.- Experience with containerization (Docker, Kubernetes).- Strong documentation, experimentation, and evaluation skills.- Experience with scraping frameworks like Playwright.- Building or utilizing ontologies with AI systems.- Experience with Databricks.- Understanding of finance related concepts. (ref:hirist.tech)

📌 Artificial Intelligence Engineer - LangChain/LangGraph (Bengaluru)
🏢 Growthsphereai Private
📍 Bengaluru