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The Harness Engineering team is seeking a Principal Engineer to lead complex cross platform initiatives and lead technical projects across geographies. Principal Engineers are recognized experts in Harness technology domain, and represent the senior technical leadership within their organization. Principal Engineers carry the responsibility of steering the course for their organizational segment, partnering with senior leadership, prioritizing initiatives to achieve a range of objectives.
Principal Engineers at Harness
Poses a careful blend of domain specific engineering expertise and world class technical leadership. There are a number of competencies that a Principal Engineer must display.
Responsibilities
Requirement
Harness is a rapidly growing startup that is disrupting the software delivery market. The Harness Software Delivery Platform includes product modules for every aspect of software delivery, including: Continuous Integration, Continuous Delivery, Feature Flags, Cloud Cost Management, Service Reliability Management, Security Testing Orchestration, Chaos Engineering, Software Engineering Insights, Continuous Error Tracking, Code Repository, Internal Developer Portal, Software Supply Chain Assurance, Infrastructure as Code Management and AI/ML infused throughout with AI Development Assistant (AIDA). The platform is designed to help companies accelerate their cloud initiatives as well as their adoption of containers and orchestration tools like Kubernetes and Amazon ECS and make software delivery easier, giving devs their nights and weekends back.
Job ID: 129358137
Skills:
Distributed Systems, Microservices, Python, Typescript, React, LLM orchestration, RAG pipelines, Next.js, generative AI features
Skills:
Python, Rabbitmq, New Relic, Django, Elk, Redis, PostgreSQL, Claude, Vector databases, Foundational LLMs, RAG, LangGraph, Fine-tuning LLMs
Skills:
PostgreSQL, Microservices, FastAPI, Asynchronous programming, Python, LangChain, model observability solutions, high-performance API design, scalable data platforms, multi-agent architectures, workflow orchestration, event-driven systems, artificial intelligence concepts, LangGraph, prompt optimization pipelines, state management solutions, AI-driven decisioning systems, context-engineering frameworks, production deployment of LLM-powered applications, secure multi-tenant architectures
Skills:
Rust, Sql, Data Modeling, Apache Airflow, C, Distributed Systems, Jira, Grafana, Python 3, Rest Apis, Linux, Prometheus, Git, AI coding assistants, Go, Cloud-native technologies, Micro-services, Data Analysis