Conversica
Himalayas · Posted 10d ago
Senior AI Software Engineer
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Indexed description
Conversica is seeking a Senior 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 high autonomy, shaping AI systems architecture and engineering standards within your project teams.
What You'll Do
- Design, implement, and ship AI-driven features and systems into production environments
- Lead technical decision-making for AI architecture, data modeling, and system integration within your domain
- 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
- Implement and advocate for best practices for applied AI engineering, including agent evaluation, interpretability, data layer design, and monitoring
- Mentor and guide other engineers, raising the bar on AI engineering quality and decision-making
- Provide input into technical strategy and roadmap discussions related to AI capabilities and 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
Qualifications & Experience
- Equivalent of 5+ 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 working with 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 Have
- 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
What We Value
- We care about what you've built, not where you learned it. If you've shipped strong software, led technical decisions under ambiguity, contributed to open source, written thoughtful technical work, or built impressive projects with modern LLM tooling - put that front and center. Show us what you've built, what problems you've wrestled with, and how you reason about tradeoffs in systems that combine LLMs with real-world constraints.
Originally posted on Himalayas
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