Senior Software Engineer, Full-Stack (Copy)

Doowii•Denver, CO

About The Position

Doowii is 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.

Requirements

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

Nice To Haves

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

Responsibilities

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
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
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
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