Varicent is hiring a Lead Software Engineer, Generative AI to help design and deliver production-grade AI solutions that support modern revenue optimization platforms.
This fully remote opportunity in Mexico is ideal for experienced software engineers who enjoy building scalable AI systems, owning end-to-end delivery, and working across cloud infrastructure, experimentation, and product development.
If you have strong software engineering foundations and want to expand your impact in Generative AI and production AI systems, this role offers an exciting opportunity.
Job Details
- Position: Lead Software Engineer, Generative AI
- Company: Varicent
- Location: Mexico (Remote)
- Employment Type: Full-Time
- Department: Engineering
About Varicent
Varicent develops Sales Performance Management (SPM) solutions that help organizations optimize revenue operations and improve business performance.
Its SaaS platform supports global businesses with tools that enable smarter go-to-market execution, performance management, and revenue growth.
Role Overview
As a Lead Software Engineer focused on Generative AI, you will contribute to designing, building, deploying, and scaling AI-enabled product capabilities.
You’ll collaborate with technical leaders and stakeholders while helping define engineering standards, quality metrics, and operational excellence practices.
Key Responsibilities
In this role, you will:
- Own end-to-end delivery for AI-enabled systems and features
- Design scalable services and production AI workflows
- Build reliable APIs, data pipelines, and backend systems
- Define testing strategies and quality evaluation frameworks
- Run experiments and translate findings into product improvements
- Improve monitoring, deployment, reliability, and operational readiness
- Mentor engineers through reviews and technical guidance
- Support cost optimization and performance improvements
Generative AI Focus Areas
Candidates should understand how modern AI applications are designed, evaluated, and deployed.
Areas of interest include:
- Prompt engineering
- Retrieval-Augmented Generation (RAG)
- Tool and function calling
- Embeddings and vector search
- Model evaluation workflows
- Fine-tuning and optimization strategies
- Privacy and responsible AI implementation
Required Qualifications
Successful candidates should have:
- 6+ years of software engineering experience
- 3+ years building and shipping production software
- Bachelor’s degree in Computer Science, Engineering, or related field
- Strong software architecture and system design experience
- Hands-on coding experience using:
- Python
- TypeScript
- APIs and services
- Data pipelines
- Cloud platform experience
- Knowledge of:
- CI/CD
- Automated testing
- Observability
- Experiment-driven development
Preferred Skills
Additional experience may include:
- GenAI and LLM workflows
- LLMOps and experiment tracking
- Prompt versioning and optimization
- Serverless AWS environments
- LangChain and LangGraph
- OpenAI, Anthropic, or Azure OpenAI platforms
- Pinecone, FAISS, or Milvus vector databases
- Open-source contributions and technical writing
How the Team Works
Varicent encourages teams to:
- Experiment rapidly and productionize validated ideas
- Focus on measurable quality and outcomes
- Own systems across development, deployment, and reliability
- Continuously improve performance, accuracy, and cost efficiency
Remote Work Expectations
This is a fully remote role; however, candidates should be prepared to align their work schedule with Eastern Standard Time (EST) business hours to support collaboration.
Benefits and Perks
Varicent offers:
- Competitive compensation packages
- Comprehensive health and insurance coverage
- Remote work flexibility
- Wellness and employee support programs
- Access to modern engineering tools and technologies
- Continuous professional development opportunities
- Global collaboration across international teams
Why Consider Varicent?
This role combines software engineering leadership with practical AI delivery in production environments. Engineers have opportunities to influence architecture, shape AI capabilities, and work on products used by organizations around the world.
If you enjoy building scalable AI systems and leading technical execution, this opportunity may be worth exploring.