Develops core AI capabilities for Atlassian’s DevAI products, including LLM-based methodologies, prompt engineering, end-to-end AI features, data preprocessing, feature engineering, experimentation, model evaluation, pipeline optimization, and monitoring. Collaborates with data scientists, software engineers, and cross-functional partner teams to solve complex problems and apply advances in machine learning and AI.
Engineering | San Francisco, United States | Remote, Remote
Working at Atlassian
Atlassians can choose where they work - whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.
As part of our team, you will play a crucial role in innovating the core intelligence solutions within our DevAI products. Your responsibilities will include (but not limited to) LLM integration, prompt engineering, and developing end-to-end AI features using cutting-edge technologies. You will collaborate closely with a diverse and highly skilled group of scientists and software engineers within our team, as well as with multiple partner teams across the company. Together, we are committed to delivering Atlassian's world-class developer AI products that will shape the future of software development.
Responsibility
General Responsibilities
These are ongoing or overarching tasks that guide the strategic and collaborative aspects of the role:
Daily Responsibilities
These tasks are more routine or technical, involving hands-on activities that need to be performed regularly:
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit
Working at Atlassian
Atlassians can choose where they work - whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.
As part of our team, you will play a crucial role in innovating the core intelligence solutions within our DevAI products. Your responsibilities will include (but not limited to) LLM integration, prompt engineering, and developing end-to-end AI features using cutting-edge technologies. You will collaborate closely with a diverse and highly skilled group of scientists and software engineers within our team, as well as with multiple partner teams across the company. Together, we are committed to delivering Atlassian's world-class developer AI products that will shape the future of software development.
Responsibility
General Responsibilities
These are ongoing or overarching tasks that guide the strategic and collaborative aspects of the role:
- Problem Solving: Identify complex challenges and provide creative solutions to advance the capabilities and functionalities of the products.
- Collaboration: Work with cross-functional teams, including data scientists and software engineers. Build and maintain sustainable partnerships with team members from various technical backgrounds.
- Communication: Communicate technical details effectively to the team and engage in technical discussions to contribute ideas and solutions.
- Continuous Learning: Stay updated with the latest research and advancements in machine learning, AI, and relevant technology applications. Apply cutting-edge knowledge and techniques to enhance product innovation and effectiveness.
Daily Responsibilities
These tasks are more routine or technical, involving hands-on activities that need to be performed regularly:
- Design and Development: Design LLM based methodology and algorithms tailored to specific product needs.
- Data Handling: Perform data preprocessing and feature engineering to improve product inputs and performance.
- Evaluation: Conduct experiments to evaluate the performance of products and use a variety of metrics and testing methods to ensure the solutions meet design specifications.
- Implementation and Optimization: Implement and optimize machine learning pipelines.
- Monitoring and Maintenance the deployed intelligence solutions to ensure they continue to perform accurately and efficiently.
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit
Similar Jobs at Atlassian
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Develop and deploy machine learning and LLM capabilities for agentic search, query understanding, search planning, and retrieval. Build evaluation datasets, improve model behavior through experimentation and fine-tuning, and optimize quality, latency, cost, and reliability. Collaborate across search, product, infrastructure, and AI teams while owning projects through production and mentoring engineers.
Top Skills:
AWSDatabricksInformation RetrievalLarge Language Models (Llms)Machine LearningNatural Language Processing (Nlp)PythonRetrieval-Augmented Generation (Rag)Search RelevanceSpark
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Develop and deploy scalable machine-learning solutions, particularly deep-learning forecasting models for company top-line metrics. Lead the full ML lifecycle from problem definition and experimentation through production deployment and improvement. Design production-grade architectures, evaluate and improve models, collaborate with cross-functional teams, explain technical concepts to varied audiences, and mentor junior engineers.
Top Skills:
Deep LearningMachine LearningMachine Learning Infrastructure
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Build and operate scalable machine learning systems for personalized recommendations, growth journeys, cross-product expansion, and sales experiences. Design models, datasets, features, evaluation frameworks, and decisioning services; run offline policy evaluations and online experiments; and monitor attribution, latency, quality, and fairness. Partner with product, engineering, data science, analytics, marketing, and sales teams to turn ambiguous growth opportunities into measurable production capabilities and strategic ML initiatives.
Top Skills:
SparkAWSDatabricksJavaPythonSQLTypescript
What you need to know about the Charlotte Tech Scene
Ranked among the hottest tech cities in 2024 by CompTIA, Charlotte is quickly cementing its place as a major U.S. tech hub. Home to more than 90,000 tech workers, the city’s ecosystem is primed for continued growth, fueled by billions in annual funding from heavyweights like Microsoft and RevTech Labs, which has created thousands of fintech jobs and made the city a go-to for tech pros looking for their next big opportunity.
Key Facts About Charlotte Tech
- Number of Tech Workers: 90,859; 6.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lowe’s, Bank of America, TIAA, Microsoft, Honeywell
- Key Industries: Fintech, artificial intelligence, cybersecurity, cloud computing, e-commerce
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (CED)
- Notable Investors: Microsoft, Google, Falfurrias Management Partners, RevTech Labs Foundation
- Research Centers and Universities: University of North Carolina at Charlotte, Northeastern University, North Carolina Research Campus
