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We are seeking a highly experienced AI Tech Lead to drive the design, architecture, anddelivery of enterprise-grade AI and Agentic AI solutions.
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The role requires deep expertise in Generative AI, Large Language Models (LLMs), RetrievalAugmented Generation (RAG), and multi-agent systems.
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The candidate will be responsible for building scalable, production-ready AI platforms andleading cross-functional teams in delivering AI-driven business solutions.
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This role is focused on AI engineering, architecture, and system design rather thantraditional data science or analytics.
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Design and own end-to-end AI system architecture including LLM-based applications,RAG pipelines, and agentic AI workflows.
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Develop and deploy scalable AI solutions using microservices architecture and API-drivendesign patterns.
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Lead the development of Agentic AI systems including multi-agent orchestration,planning, reasoning, and tool integration.
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Implement LLM orchestration frameworks including LangChain, LlamaIndex, AutoGen,CrewAI, or similar.
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Build and optimize semantic search systems using embeddings and vector databases.
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Establish and drive MLOps and LLMOps practices including CI/CD, model deployment,monitoring, and observability.
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Integrate AI solutions with enterprise platforms such as ERP, CRM, and data lakes.
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Drive reusable AI components, frameworks, and accelerators for enterprise adoption.
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Mentor AI engineers and guide teams on architecture, design patterns, and bestpractices.
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Collaborate with stakeholders to translate business problems into scalable AI solutions.
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Continuously evaluate emerging AI technologies and drive innovation in AI platforms.
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AI / GenAI / LLM:
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Strong hands-on experience with Large Language Models (LLMs) such as GPT, Claude,Gemini.
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Experience in building Generative AI applications using RAG (Retrieval-AugmentedGeneration).
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Expertise in prompt engineering, prompt tuning, and evaluation frameworks.
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Experience with fine-tuning techniques such as LoRA, PEFT, and model optimization.
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Hands-on experience with OpenAI, Azure OpenAI, AWS Bedrock, or similar APIs.
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Agentic AI:
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Experience in building AI agents and multi-agent systems.
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Hands-on experience with LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI,Semantic Kernel.
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Understanding of tool calling, function calling, and agent orchestration.
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Experience with memory systems, context handling, and reasoning workflows.
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Ability to design planning agents and autonomous decision-making systems.
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Architecture & Engineering:
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Strong experience in AI system architecture and scalable distributed systems.
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Experience with microservices architecture, REST APIs, and event-driven systems.
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Ability to design real-time and batch AI pipelines.
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Experience in building production-grade AI platforms and services.
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MLOps / LLMOps:
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Experience with MLflow, Kubeflow, Databricks, SageMaker.
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Strong understanding of CI/CD pipelines for AI systems.
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Experience in model deployment, monitoring, drift detection, and observability.
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Experience in model versioning and lifecycle management.
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Data & Retrieval:
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Experience with vector databases such as FAISS, Pinecone, Weaviate, Chroma.
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Strong understanding of embeddings, semantic search, and retrieval pipelines.
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Experience with structured and unstructured data processing.
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Knowledge of data pipelines and ETL processes.
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Programming & Cloud:
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Strong proficiency in Python.
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Experience with PyTorch, TensorFlow, HuggingFace Transformers.
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Experience with FastAPI or Flask for building AI services.
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Hands-on experience with Azure, AWS, or GCP.e. Experience with Docker and Kubernetes.f. Understanding of GPU-based workloads and scalable infrastructure.
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Proven experience leading AI/ML engineering teams.
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Strong ability to define architecture and drive technical decisions.
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Experience in stakeholder management and cross-functional collaboration.
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Ability to translate business requirements into AI solutions.
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Experience delivering enterprise-grade AI systems in production environments.
Good to have:
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Experience in building enterprise AI platforms or AI CoE.
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Exposure to RPA + AI and intelligent automation.
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Experience in document AI, OCR, and multimodal AI.
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Domain experience in Fintech, ERP, Manufacturing, or Healthcare.
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Understanding of AI governance, compliance, and security.
Avaali offers a high degree of autonomy and control to employees to execute yourresponsibilities. We offer each employee significant opportunities for advancement and growthas we engage senior audiences in customer organizations to transform their business via emergingtechnologies. We offer great job stability – several of our employees have been with us for over5+ years.
