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.
Key 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
What You’ll Build
- Agentic system design: orchestration, tool use, state/memory, multi-step workflows
- Evals + quality: harnesses, regression tests for prompts/agents, online/offline metrics, iteration loops
- Guardrails: hallucination mitigation, grounding, HITL review, safe degradation paths
- Production operations: cost/latency tradeoffs, caching, rate-limits, fallbacks, observability, incident response
- Retrieval + data foundations: RAG choices, indexing, freshness, data quality constraints, data layer design
Qualification & Experience
- 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 back