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Evnek Technologies

AI Lead

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Job Title: AI<\/span> <\/span><\/span><\/span>Lead<\/span><\/span> <\/span><\/span><\/span><\/span>
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Experience:<\/span> <\/span><\/span>8\u201310 Years<\/span> <\/span><\/span><\/span><\/span>
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Location:<\/span> <\/span><\/span>Remote<\/span><\/span><\/span> <\/span><\/span>
<\/span><\/span>Notice Period:<\/span> <\/span><\/span>Immediate Joiners Only<\/span><\/span><\/span> <\/span><\/span>
<\/span><\/span>About the Role<\/span><\/span><\/span>
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We are seeking an experienced<\/span> <\/span><\/span><\/span><\/span>AI<\/span> <\/span><\/span><\/span>Lead<\/span><\/span><\/span> <\/span><\/span>to design, build, and scale next\-generation<\/span> <\/span><\/span><\/span><\/span>Agentic AI systems<\/span><\/span><\/span> <\/span><\/span>capable of autonomous reasoning, planning, and task execution. This role requires a strong blend of<\/span> <\/span><\/span>expertise<\/span> <\/span><\/span>in Generative AI, Machine Learning,<\/span> <\/span><\/span><\/span>MLOps<\/span><\/span>, and cloud\-native architectures.<\/span><\/span><\/span>
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As an AI Lead, you will drive the technical vision for intelligent AI solutions,<\/span> <\/span><\/span><\/span>architect<\/span><\/span> <\/span><\/span>multi\-agent systems, lead engineering teams, and ensure successful deployment of production\-grade AI applications. You will work closely with cross\-functional stakeholders to deliver scalable, reliable, and innovative AI\-powered products.<\/span><\/span><\/span>
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Key Responsibilities<\/span><\/span><\/span>
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Agentic AI & LLM Engineering<\/span><\/span><\/span>
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  • Design, develop, and orchestrate multi\-agent AI systems capable of autonomous reasoning and decision\-making.<\/span><\/span><\/span>
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    • Architect and implement LLM\-powered workflows using frameworks such as<\/span> <\/span><\/span><\/span>LangChain<\/span><\/span>,<\/span> <\/span><\/span><\/span>LangGraph<\/span><\/span>,<\/span> <\/span><\/span><\/span>CrewAI<\/span><\/span>, and<\/span> <\/span><\/span><\/span>AutoGen<\/span><\/span>.<\/span><\/span><\/span>
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      • Develop and<\/span> <\/span><\/span>optimize<\/span> <\/span><\/span>Retrieval\-Augmented Generation (RAG) pipelines for enterprise\-scale AI applications.<\/span><\/span><\/span>
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        • Design agent memory architectures, context management strategies, and long\-term knowledge retention mechanisms.<\/span><\/span><\/span>
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          • Integrate external tools, APIs, databases, and third\-party services into AI agent workflows.<\/span><\/span><\/span>
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            • Optimize<\/span> <\/span><\/span>prompt engineering strategies and implement advanced prompting techniques for production use cases.<\/span><\/span><\/span>
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              Machine Learning & AI Development<\/span><\/span><\/span>
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              • Build, train, deploy, and<\/span> <\/span><\/span>maintain<\/span> <\/span><\/span>machine learning models for classification, ranking, recommendation, anomaly detection, and predictive analytics.<\/span><\/span><\/span>
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                • Fine\-tune foundation models and LLMs using techniques such as<\/span> <\/span><\/span><\/span>LoRA<\/span><\/span>, PEFT, quantization, and instruction tuning.<\/span><\/span><\/span>
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                  • Develop scalable NLP<\/span> <\/span><\/span><\/span>solutions<\/span><\/span> <\/span><\/span>leveraging<\/span> <\/span><\/span>transformers, embeddings, and vector search technologies.<\/span><\/span><\/span>
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                    • Define model evaluation frameworks using metrics such as F1 Score, Precision, Recall, AUC, and other business\-specific KPIs.<\/span><\/span><\/span>
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                      • Implement feature engineering, model validation, and experimentation workflows.<\/span><\/span><\/span>
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                        MLOps<\/span><\/span> <\/span><\/span>& Infrastructure<\/span><\/span><\/span>
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                        • Establish end\-to\-end<\/span> <\/span><\/span><\/span>MLOps<\/span><\/span> <\/span><\/span>pipelines for model training, deployment, monitoring, versioning, and governance.<\/span><\/span><\/span>
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                          • Implement CI/CD workflows for AI and ML systems.<\/span><\/span><\/span>
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                            • Deploy AI solutions on cloud platforms including AWS, GCP, and Azure.<\/span><\/span><\/span>
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                              • Build scalable infrastructure using Docker, Kubernetes, Terraform, and cloud\-native services.<\/span><\/span><\/span>
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                                • Ensure observability, monitoring, and performance optimization of AI systems.<\/span><\/span><\/span>
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                                  Leadership & Architecture<\/span><\/span><\/span>
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                                  • Lead architecture decisions for AI and ML initiatives across the organization.<\/span><\/span><\/span>
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                                    • Mentor AI/ML engineers and<\/span> <\/span><\/span>provide<\/span> <\/span><\/span>technical guidance on best practices and emerging technologies.<\/span><\/span><\/span>
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                                      • Collaborate with product, engineering, and business teams to align AI capabilities with strategic<\/span> <\/span><\/span>objectives.<\/span><\/span><\/span>
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                                        • Drive innovation through evaluation and adoption of emerging AI technologies and research advancements.<\/span><\/span><\/span>
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                                          Required Qualifications<\/span><\/span><\/span>
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                                          • 8\u201310 years of overall experience in Software Engineering.<\/span><\/span><\/span>
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                                            • Minimum<\/span> <\/span><\/span>4+ years of hands\-on experience in AI/ML engineering and<\/span> <\/span><\/span><\/span>production<\/span><\/span> <\/span><\/span>AI systems.<\/span><\/span><\/span>
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                                              • Proven<\/span> <\/span><\/span>expertise<\/span> <\/span><\/span>in building and deploying Agentic AI and Autonomous AI solutions.<\/span><\/span><\/span>
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                                                • Strong experience with Large Language Models (LLMs), prompt engineering, fine\-tuning, and model optimization.<\/span><\/span><\/span>
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                                                  • Proficiency<\/span> <\/span><\/span>in Python and modern AI frameworks including<\/span> <\/span><\/span><\/span>LangChain<\/span><\/span>,<\/span> <\/span><\/span><\/span>LangGraph<\/span><\/span>,<\/span> <\/span><\/span><\/span><\/span><\/p><\/li><\/ul><\/div><\/span>