Staff AI Software Engineer

Conversica

5h•Remote

About The Position

Conversica is seeking a Staff AI Software Engineer to design, build, and scale production-grade AI systems that deliver direct customer and business value. This senior individual contributor role emphasizes pragmatic, product-focused, customer-driven thinking, with a focus on translating real-world problems into reliable, maintainable, and scalable AI-driven solutions. This role operates with a high degree of autonomy and technical influence, shaping AI and systems architecture, engineering standards, and best practices across the organization.

Requirements

Equivalent of 8+ years of professional software engineering experience, with significant focus on applied AI.
Proven experience deploying LLM-powered systems/applications in production environments
Strong proficiency in Python, and experience building production LLM applications (agents/tool use, retrieval, evals, monitoring)
Experience working with large datasets and navigating real-world data quality challenges
Strong system design, problem-solving, and architectural decision-making skills
Experience designing agent architectures, tool interfaces, and orchestration patterns
Desire to continually follow and experiment with cutting edge AI technologies and tooling for use across all phases of the software development lifecycle (i.e. during design, analysis, coding, deployment, QA, etc.)
Strong background in modern cloud-based architectures.

Nice To Haves

Experience applying AI solutions in a B2B SaaS environment
Experience interacting with data from Marketing Automation Platforms (MAPs), Customer Resource Management Systems (CRMs), and Customer Data Platforms (CDPs)
Experience deploying AWS infrastructure, and production use of Terraform, EKS, Postgres, MySQL, Datadog, and GitLab

Responsibilities

Design, implement, and ship AI-driven features and systems into production environments
Own technical decision-making for AI architecture, data modeling, and system integration
Partner closely with Product, Engineering, and other stakeholders to translate business needs into scalable technical solutions
Identify and address reliability, scalability, performance, and observability challenges in AI systems
Establish and evolve best practices for applied AI engineering, including agent evaluation, interpretability, and reliability, data layer design, monitoring, explainability, and continuous improvement
Mentor and guide other engineers, raising the bar on AI engineering quality and decision-making
Contribute to technical strategy and roadmap discussions related to AI capabilities and overall platform evolution