AI Engineer- Bangalore (Telangana)

Hi, We are having opening for AI Engineer- Bangalore Working Days: Monday Friday Job Timing: Day shift Position / DesignationAI EngineerQualificationBachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related fieldYears of Experience4+ years of hands-on experience with LLMs and GenAI in production settings.Permanent / Contract (If contract, period )Permanent Full TimeOffice / Remote / Hybrid Chennai, Bangalore, Hyderabad Bangalore - bellandur - Latent View office Chennai - , Rajiv Gandhi SalaiTaramani, Chennai - Latent View office Hyderabad - Hitech city - client office Number of post4GenderMale / FemaleAnnual CTC / SalaryAs per market standardsSelection Process1- Total 3 Technical round 2- 2 rounds evaluation with LV (we can plan to take this together based on panel availability) & 1 with client Job Role & Responsibility 1. Solution Architecture & Deployment Design and deploy scalable, secure GenAI architectures integrated into customer-facing products. Build REST APIs for AI/ML models and deploy them in containerized environments (Docker, Kubernetes) on cloud platforms (AWS, Azure, GCP). 1. GenAI & LLM Development Fine-tune and optimize generative models including GPT, VAEs, GANs, and transformer-based architectures. Apply techniques like Retrieval-Augmented Generation (RAG) and prompt engineering to enhance model performance and relevance. Work with both commercial and open-source LLMs (e.g., GPT-4, Claude, LLaMA 3.2, Phi). 1. Agentic AI Integration Primary Focus: Build, deploy, and optimize AI agents leveraging frameworks such as LangChain, LangGraph, CrewAI, AgentFlow, and Autogen. Implement orchestration strategies, multi-agent collaboration, tool integration, and memory/state management. Drive experimentation to create autonomous or semi-autonomous agents that solve real business workflows and decision-making processes. 1. MLOps & Performance Optimization Establish MLOps pipelines covering model lifecycle: training, CI/CD, monitoring, and retraining. Use tools like Git, Docker, Kubernetes, and vector DBs to ensure efficient and reliable deployment. Optimize resource utilization and infrastructure costs. 1. Cross-Functional Collaboration Partner with engineering, data science, and product teams to align technical solutions with business goals. Effectively communicate complex concepts across diverse technical and non-technical audiences. Stay current with industry advancements and drive innovation in GenAI and AI agent strategy. Skills Solid proficiency in Python, SQL, and GenAI frameworks (e.g., LangChain). Hands-on experience in building and deploying AI agents with orchestration, tool use, and state management. In-depth knowledge of LLM architecture, RAGs, embeddings, prompt tuning, and vector databases, agentic AI patterns (ReAct, tool-calling agents, multi-step reasoning, guardrails) Experience with cloud platforms (AWS, Azure, GCP) and containerization. Strong analytical, problem-solving, and communication skills. Data integration experience REST APIs, Google APIs, SQL databases. Comfortable moving data between systems. Experience in Web development: FastAPIs, Typescript, async patterns, building production APIs, React, node.js, Component architecture, hooks, state management, consuming streaming APIs (SSE/WebSocket) Exposure to agentic AI tools and multi-agent workflows (e.g., CrewAI, LangGraph, Autogen). Familiarity with MLOps and AI deployment best practices. Experience in client-facing or cross-functional AI initiatives. Publications, open-source contributions, or demonstrable projects showcasing AI agent development.Joining DateNeed Immediate to 1 Month .