TaxValet is seeking an AI Engineer II to lead the design, development, and ownership of AI-powered internal platforms and systems. In this remote role, you will take on end-to-end ownership of complex projects, from problem discovery to production rollout, translating ambiguous business problems into scalable, AI-enabled solutions.

What You'll Do

Lead the design, development, and ownership of AI-powered internal platforms and systems, including initiatives built from the ground up.
Own end-to-end delivery of complex projects, from problem discovery and system design through production rollout and iteration.
Design and implement AI-driven features, intelligent automation, and orchestration systems that enhance customer experiences and compound productivity across teams.
Embed AI capabilities into customer-facing products, internal tools, and operational workflows, ensuring solutions integrate naturally and deliver measurable value.
Build full-stack systems spanning backend services, APIs, data layers, and frontend interfaces.
Translate ambiguous business and operational problems into scalable, maintainable, AI-enabled technical solutions.
Apply strong systems thinking to ensure reliability, performance, security, permissions, and auditability across platforms.
Collaborate closely with engineers, teams, and stakeholders across the company to identify high-impact opportunities and drive adoption.
Participate in production support and incident response for owned systems, helping define and uphold reliability and operational best practices.
Mentor AI team members through code reviews, design feedback, and hands-on guidance, raising the overall quality bar of the team.

What We're Looking For

3–5 years of professional experience in software engineering, AI engineering, platform engineering, or related roles.
Hands-on experience designing, building, and shipping AI-powered systems into production environments.
Strong proficiency in Python, SQL, and frontend frameworks such as React.
Proven experience designing and owning production-grade full-stack systems.
Experience working with distributed systems, internal platforms, or complex data workflows.
Ability to operate effectively in ambiguous problem spaces and drive solutions with minimal direction.

Nice to Have

Experience building AI-first platforms or internal products from scratch, including early architectural decisions.
Strong foundation in core machine learning and data science principles, including supervised/unsupervised learning, feature engineering, model evaluation, and statistical inference.
Experience with transformer architectures (BERT, GPT, etc.) and understanding of attention mechanisms, tokenization, and fine-tuning strategies for domain-specific applications.
Experience developing AI-assisted or agentic systems that interact with tools, data, or workflows.
Familiarity with embeddings and vector representations, including text embeddings, similarity search, and integration with vector databases (Pinecone, Weaviate, pgvector, or similar).
Experience with NLP techniques including text classification, named entity recognition, semantic search, and information extraction.
Familiarity with cloud-native development using AWS.
Understanding of prompt engineering, retrieval-augmented generation (RAG), and LLM application patterns.
Experience with containerized systems and orchestration tools such as Docker and Kubernetes.
Exposure to CI/CD pipelines and modern development workflows (e.g., GitLab).
Experience with Golang is a plus (or willingness to learn).