Jobs at Armakuni

Lead client discovery and consult on technical/business needs, develop proposals and solution decks, collaborate on high-level architecture with solution architects, research Cloud/Data/GenAI trends, and coordinate across sales and delivery for successful pre-sales engagement.

Lead architecture, design, and development of scalable Python-based, cloud-native applications. Drive microservices, serverless, and distributed system implementations, optimize databases and performance, enhance CI/CD/DevOps, and mentor engineering teams while ensuring secure, modular code and alignment with business goals.

Design, build, and scale generative AI and ML solutions including LLM fine-tuning, RAG pipelines, model training and deployment on AWS SageMaker/Bedrock, experiment tracking, and computer vision tasks. Work with vector databases, ML libraries and deep learning frameworks, and develop REST APIs and production integrations.

Design and implement CI/CD pipelines, manage cloud infrastructure across AWS and Azure, implement IaC and Kubernetes, improve observability and security (DevSecOps), support application deployments, migrations, and operational monitoring.

Lead large backend engineering teams, provide solutions architecture, troubleshooting, and technical implementation guidance; occasionally develop code; drive improvements in tech stacks, enforce best practices, deliver training, and mentor developers.

Lead technical vision and delivery of AI/ML and Generative AI solutions (LLMs, computer vision, forecasting). Mentor engineers, design architectures, build RAG pipelines, manage ML lifecycle, deploy and monitor models on AWS, and collaborate with stakeholders to translate business problems into scalable AI systems.

Design and implement CI/CD pipelines, manage multi-tier AWS cloud infrastructure using IaC, containerize applications with Docker/Kubernetes, troubleshoot deployments, manage releases and environment configurations, and promote DevOps best practices across development teams.

Design and maintain enterprise data architecture, create logical/physical data models, design databases and warehouses, oversee ETL/ELT integrations, enforce data governance and security, evaluate data technologies, collaborate with stakeholders, and document data flows and performance tuning.