Generative AI Tech Lead – LLMs, MLOps, AWS

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Provectus

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Artificial Intelligence • SaaS

Provectus is an artificial intelligence consultancy and solutions provider that helps businesses transform through AI. Offering both a use case and a platform approach, Provectus integrates AI into organizations to achieve unique business objectives and technical capabilities. Their solutions are cloud-native, vendor-agnostic, and open, allowing for deployment in customer's cloud without restrictive licenses. With applications in industries like retail, manufacturing, and healthcare, Provectus delivers AI-powered use cases and turnkey solutions to drive innovation and efficiency. They also offer consulting, customization, and managed AI services.

501 - 1000 employees

Founded 2012

🤖 Artificial Intelligence

☁️ SaaS

📋 Description

• Lead, mentor, and grow a team of 5–10 ML, Data, and Software Engineers • Define and drive the technical roadmap for ML/AI initiatives • Foster a high-performance culture focused on ownership, learning, and engineering excellence • Work closely with Product, Data, and Platform teams to deliver end-to-end AI systems • Design, fine-tune, and deploy LLMs and ML models for real production use cases • Build systems for RAG, summarization, text generation, entity extraction, and other NLP/LLM workflows • Explore and implement emerging GenAI/LLM techniques and infrastructure • Contribute across the ML stack: NLP, deep learning, CV, RL, and classical ML • Architect and operate scalable ML/AI systems using AWS (SageMaker, Bedrock, Lambda, S3, ECS/ECR…) • Optimize model training, inference pipelines, and data workflows for scale, cost, and latency • Implement MLOps/LLMOps best practices, CI/CD pipelines, monitoring, and automation • Ensure security, reliability, observability, and compliance across ML workloads • Lead the full ML lifecycle: research - experimentation - prototyping - production - maintenance • Perform code reviews, lead architecture discussions, and ensure engineering best practices • Troubleshoot and optimize production ML systems • Communicate project status, risks, and decisions to stakeholders and leadership

🎯 Requirements

• 5+ years of hands-on experience in Machine Learning, Deep Learning, or NLP • 2+ years in a technical leadership or team lead role • Strong expertise with **LLMs** (Hugging Face, OpenAI, Anthropic) and modern NLP stacks • Strong hands-on experience with **AWS ML ecosystem** (SageMaker, Bedrock, Lambda, S3, ECS/ECR) • Excellent Python engineering skills and proficiency with PyTorch or TensorFlow • Experience building **ML systems in production**, not just research • Solid knowledge of MLOps/LLMOps tools, pipelines, and deployment best practices • Strong architectural thinking and ability to design scalable ML systems • Excellent communication skills and ability to lead cross-functional teams • Passion for mentoring engineers and raising the technical bar • Experience with Bedrock Agents, RAG pipelines, agentic workflows, or vector search

🏖️ Benefits

• Sing-up bonus • 10% Annual bonus • Long-term B2B collaboration • Fully remote setup • Comprehensive private medical insurance or budget for your medical needs. • Paid sick leave, vacation, and public holidays • Continuous learning support, including unlimited AWS certification sponsorship