Senior AI Engineer

About Dovetail

Dovetail is a rapidly growing global company on a mission to improve the quality of every thing. Our AI-native customer intelligence platform helps thousands of teams from Fortune 500 companies to innovative startups to bring together customer insights from across their organization.

We capture every sales call, survey, report, interview, support ticket, renewal call, usability test, and app review, and transform that raw data into actionable insights your product team can leverage. By helping our customers truly understand their users, we empower them to build better products, services, and experiences.

We’re seeking ambitious problem solvers from diverse backgrounds who are valued for their experience, passionate about their craft, and excited about the work we’re undertaking.

The Role: Senior AI Engineer

We're looking for a Senior AI Engineer to join our Data Ingestion & AI team, focusing on the next generation of how Dovetail converts huge amounts of unstructured data into actionable insights. This team has an extremely high impact and is faced with the challenge of building an industry-leading AI product while providing simplicity to our customers.

What You’ll Do

• Join our Data Ingestion & AI team. You'll be a crucial part of our AI team, working closely with your engineering manager and other engineers to evolve our AI feature set of Dovetail's product.
• Driving AI enablement. Enabling and empowering others to build and improve AI features across the product teams and greater organisation.
• R&D. You’ll be given capacity to stay on top of new technologies and trends to influence the product roadmap.
• Mentor and support other engineers. We're growing quickly and as a senior engineer, you'll assist in optimizing the team to continually improve their software practices through code review, pair programming, etc to support career growth.
• Foster a culture of pragmatism. You'll maintain and foster a pragmatic approach to software development whilst also collaborating towards the establishment of detailed guidelines and standards for product development processes based on industry best practices and your experience.

What You’ll Bring

• Experience building ML products. You'll have hands-on exposure to building, designing, developing, and researching Machine Learning systems - especially Large Language Models (LLMs) and retrieval-augmented generation (RAG) pipelines. This will include productionizing them with technology like OOL, TypeScript, React, GraphQL, Node, ProseMirror, PostgreSQL and AWS.
• Performance evaluation and improvements. Ability to dig deep into the data and ML pipeline (traditional and/or LLMs) to understand, evaluate and improve the results.
• You are pragmatic and flexible. Like your new teammates, you're used to doing what's necessary to get the job done. You'll need to be comfortable with ambiguity, resourceful in solving problems, and able to adjust to shifting deadlines and project goals.
• When you do it, you nail it. You share our keen eye for quality. You don't half-ass your work, instead what you ship is top-notch. You cut scope before cutting quality.
• Excellent, concise communicator. You can easily convey your thoughts, opinions, and feelings with your product team and have the ability to articulate effort vs impact tradeoffs.
• You know how to build great software. 5 years+ of software engineering experience using Object Oriented languages. Bachelor of Computer Science or equivalent industry experience.

Nice To Have

• Search engines & NLP expertise. Strong background in search technologies (vector and semantic search), information retrieval, and natural language processing.
• Real-time systems. Practical knowledge in productionizing chatbots or real-time LLM systems.
• Cost optimization. Experience in optimizing costs for model deployment and maintenance.
• Recommendation systems. Experience in building and optimizing recommendation systems, including search result ranking and custom homepages.
• Rapid product development. You’ve worked in small nimble teams, building rapidly built high quality software in start up environments.

Benefits at Dovetail

• Equity for everyone. Along with a competitive base salary, we offer options to keep us focused on driving long-term impact.
• An environment designed for doing your best work, wherever you are. Our Sydney office is designed to maximize in-person first collaboration, while our US team is supported with a flexible remote set up.
• Join our community. Find your people in a Doveclub, bond with your team on the regular, celebrate small wins, big milestones and cultural events with the whole company.
• Learn & Thrive. Quench your thirst for knowledge with our generous L&D allowance or get support to Thrive, not just survive, using our wellness budget.
• Ample PTO. Time off for the hard work you put in. 4 weeks accrued leave, floating public holidays and additional Kit Kat days throughout the year.
• Work from anywhere. Up to 4 weeks per year to do your job anywhere in the world.
• Generous parental leave. We offer up to 20 weeks of paid parental leave to support new parents.
• 4 weeks at 4 years. 4 years is a long time in tech, and we value loyalty. Take a well-earned break of 4 weeks off on Dovetail.
• Stellar benefits for those located in the US. Comprehensive health, dental, vision, 401(K) and more offered through Sequoia.

Diversity & Inclusion

At Dovetail, we’re passionate about building and fostering an environment where every team member feels supported and valued. We celebrate individualism, welcoming everyone to show up as their authentic selves every day. It’s no secret that diversity builds the best teams, large or small, so we highly encourage applications from people who identify as part of an underrepresented group.

Dovetail's Stance on AI

At Dovetail, we expect a proactive and thoughtful approach to AI. We look for people who are curious, pragmatic, and eager to integrate AI into their everyday work.

Key skills/competency

• Machine Learning
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Production ML systems
• AWS
• TypeScript
• GraphQL
• PostgreSQL
• Natural Language Processing (NLP)
• Software Engineering
• Object-Oriented Languages