Design, build, evaluate, and operate AI-powered systems including LLM orchestration, retrieval/RAG, embeddings, and vector search. Develop scalable backend services, APIs, data pipelines, and evaluation frameworks. Improve observability, reliability, and performance of AI workflows while collaborating with frontend, data, and product teams to deliver conversational analytics and natural-language-driven features.
About Doowii
About the Role
What You’ll Work On
Requirements
Doowii is building a conversational analytics platform for education. We enable non-technical users to query complex datasets using natural language, accelerating decision making, data exploration, and intervention planning. Doowii sits at the intersection of data infrastructure, AI, and education.
We are seeking strong full-stack engineers who are proficient in web frameworks, backend development, and infrastructure. As an Applied AI Software Engineer, you'll help design, build, evaluate, and operate the AI-powered systems that transform natural language into actionable insights. Applicants must demonstrate technical mastery, architectural skills, mentoring abilities, and independence.
You'll work across Doowii's tech stack, from LLM orchestration and retrieval systems to backend APIs, data pipelines, and customer-facing product experiences.
Doowii engineering is critical in the end-to-end development of the Doowii platform, applications, and systems, from designing the user interface to managing our systems and infrastructure.
AI Systems & Product Development
- Design and implement AI-powered product capabilities using large language models, embeddings, retrieval systems, and agent workflows
- Build and maintain evaluation frameworks to measure AI quality, accuracy, reliability, and customer impact
- Improve prompt strategies, tool usage, retrieval quality, and agent behavior
- Develop systems for semantic search, retrieval-augmented generation (RAG), and conversational analytics
- Experiment with new models, frameworks, and AI techniques to improve platform capabilities
- Partner with product and engineering teams to translate customer needs into AI-driven solutions
Backend & Platform Engineering
- Build scalable backend services and APIs that support AI workflows and customer-facing applications
- Design and maintain services that orchestrate LLM interactions, retrieval systems, and external tools
- Develop and optimize data processing workflows that support AI-powered experiences
- Improve observability, reliability, testing, and deployment practices for AI systems
- Contribute to architecture decisions across application, infrastructure, and data layers
Data & Retrieval Infrastructure
- Build and maintain retrieval pipelines, embedding workflows, and vector search systems
- Design data models and indexing strategies that improve AI accuracy and performance
- Work with structured and unstructured datasets to support analytics and natural-language experiences
- Optimize storage, retrieval latency, and evaluation workflows
Full-Stack Collaboration
- Contribute to frontend and user-facing product features when needed
- Partner closely with frontend, backend, data, and product teams
- Help shape the user experience of AI-powered features and workflows
- Bachelor's degree in Computer Science, Engineering, Machine Learning, Data Science, or related field (or equivalent practical experience)
- 3+ years of professional software engineering experience
- Strong proficiency in Python
- Experience building and maintaining production software systems
- Experience working with LLM APIs and modern AI application frameworks
- Experience implementing retrieval, embeddings, vector search, or RAG workflows
- Experience designing APIs and backend services
- Strong SQL and data modeling skills
- Experience with cloud platforms such as AWS, GCP, or Azure
- Experience evaluating AI system quality, reliability, or performance
- Strong problem-solving skills and comfort working across multiple technical domains
Bonus points if you have:
- Masters in computer engineering
- Experience in any of the following areas:
- building agent-based systems or tool-calling workflows
- developing LLM evaluation frameworks, automated testing, or benchmark systems
- fine-tuning models or working with open-weight models
- working with vector databases such as Pinecone, Weaviate, pgvector, OpenSearch, or equivalent
- building analytics platforms or data-intensive applications
- working with Airflow, Dagster, dbt, Kafka, Spark, Iceberg, ClickHouse, BigQuery, or Snowflake
- managing complex workflows with prompt engineering, structured outputs, and AI safety/reliability techniques
- working with conversational interfaces, search systems, or natural-language-driven products
The base pay range for this role is $140,000 – $180,000 per year.
We’re open to adjusting the role level based on your experience and expertise. If you do not fulfill all requirements in the job description, we encourage you to submit your application nonetheless. Doowii employees are required to successfully pass a background check upon being hired.
Why work at Doowii
- Competitive compensation
- New-hire equity grant
- Open PTO policy & company holidays,
- Medical, dental, and vision benefits for you and your family
- A mission-driven culture and community
- Remote-work environment
Equal Opportunity
Doowii is an Equal Opportunity Employer and values diversity in our workforce. We believe that a diverse and inclusive workplace fosters innovation, creativity, and collaboration. We do not discriminate based upon race, religion, color, national origin, sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, education, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics
To help protect the integrity of our remote hiring process and safeguard access to student and school data, candidates may be asked to complete a brief live identity verification step prior to technical interviews.
Doowii Boulder, Colorado, USA Office
Boulder, Colorado, United States
Similar Jobs
Big Data • Fintech • Mobile • Payments • Financial Services
Lead a team of Customer Advocacy Associates to resolve complex escalations, own QA and vendor performance, manage SLAs/KPIs, drive cross-functional initiatives, analyze complaint trends, and implement scalable process and product improvements to enhance customer outcomes and reduce complaint rates.
Artificial Intelligence • Fintech • Payments • Business Intelligence • Financial Services • Generative AI
Lead and scale a team of full‑cycle Account Executives to acquire and close SMB customers. Own revenue, pipeline health, deal quality, forecasting, and coaching across discovery, negotiation, and close. Build processes, metrics, CRM discipline, and a data/AI-driven operating cadence to improve win rates, deal velocity, and pipeline quality.
Artificial Intelligence • Fintech • Payments • Business Intelligence • Financial Services • Generative AI
Lead full sales cycle for US SME customers across ecommerce, SaaS, and professional services: prospect, negotiate, close, onboard, and ramp accounts; translate technical product value; exceed revenue targets; collaborate with internal teams; represent Airwallex at events; and refine scalable sales processes.
Top Skills:
Crm SystemsSales Enablement ToolsSalesforce
What you need to know about the Colorado Tech Scene
With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute
