Ai Lead

Job Title: AI Engineering Lead Location: Chandigarh (On-site) Experience: 47 years Employment Type: Full-time Role Overview We are looking for an AI Lead Engineer to spearhead our artificial intelligence initiatives and provide technical leadership to a high-performing engineering team. In this role, you will split your time between architecting scalable AI systems, hands-on coding, and mentoring engineers. You will be the technical anchor for our AI products, ensuring we move swiftly from POC to production-grade solutions. Key Responsibilities Technical Leadership & Architecture: Design and architect robust AI/ML solutions (specifically Generative AI, RAG pipelines, and Agentic workflows) that are scalable and cost-effective. Hands-on Development: Actively contribute to the codebase, implementing core algorithms, setting up advanced RAG retrieval strategies, and integrating LLMs into our product ecosystem. Team Mentorship: Lead code reviews, enforce engineering best practices, and guide junior engineers/data scientists on technical problem-solving. MLOps: Bridge the gap between research and production. Oversee model deployment, monitoring, and optimization (latency, token usage, accuracy) on cloud infrastructure. Collaboration: Work closely with Product Managers and Leadership to translate business requirements into technical AI specifications and roadmaps. Requirements Required Skills Experience: 47 years of total experience in Software Engineering or Data Science, with at least 2+ years dedicated to Applied AI/ML or Generative AI. Core Tech Stack: Expert proficiency in Python and solid grasp of modern AI frameworks (LangChain, LlamaIndex, PyTorch, or TensorFlow). Generative AI Expertise: Proven experience building RAG (Retrieval-Augmented Generation) systems, working with Vector Databases (Pinecone, Chroma, Milvus), and prompting/tuning LLMs (OpenAI, Anthropic, Llama). System Design: Strong understanding of API design (FastAPI/Flask), database schema design (SQL & NoSQL), and microservices architecture. Leadership: Experience mentoring developers, leading technical sprints, or managing technical decision-making for a small team. Nice to Have Experience with Agentic AI frameworks (LangGraph, CrewAI). Solid MLOps background (AWS SageMaker, Docker, Kubernetes, CI/CD for ML). Experience with model fine-tuning (LoRA, QLoRA) or deploying open-source models (vLLM, Ollama). Previous startup experience. Benefits What We Offer Opportunity to define the technical direction of innovative AI-driven products. A clear growth path into Principal Engineer roles. A collaborative, fast-paced environment where your code ships to production quickly. Competitive compensation and the chance to work with the latest AI tech stack.


Key Responsibilities Design and implement AIOps pipelines for telemetry ingestion, analytics, and alerting Build AI-driven observability capabilities for anomaly detection and incident diagnostics Develop ML/LLM workflows using Ray, PyTorch Lightning, vLLM, or SGLang Implement automation for: anomaly detection event correlation predictive maintenance Build and enhance self-healing infrastructure and auto-remediation runbooks Optimize model serving and LLM inference using vLLM, Ray Serve, Triton, Kubernetes Implement real-time streaming pipelines using Kafka, Spark, or Flink Integrate CI/CD for AI workflows with MLflow, Kubeflow, or Airflow Work closely with SRE, platform, and AI engineering teams Contribute to AIOps solution evaluation and PoCs for enterprise platforms Participate in architecture discussions, design reviews, and performance optimizatio