Senior Software Engineer, AI

About the Role

The AI Engineering team at Lattice is focused on building cutting-edge systems that power AI capabilities across the company. You will be working closely with product and design teams to deliver exceptional user experiences and drive business outcomes. The team is committed to innovation, collaboration, and continuous learning, making this a great opportunity for professionals looking to grow their skills and expertise.

Lattice's engineering team values ownership, accountability, and open communication. As a senior software engineer, you will be expected to own projects end-to-end, drive them to completion, and collaborate with stakeholders to ensure successful outcomes.

What You Will Do

• Design and ship a robust, end-to-end AI evaluation framework, covering offline evaluations, production tracing, and human-in-the-loop feedback loops.
• Define and instrument key metrics to measure AI performance, including agent task completion, hallucination rates, response quality, user engagement, and downstream business outcomes.
• Build and maintain evaluation datasets, test harnesses, and automated scoring pipelines to catch regressions before they ship.
• Identify and surface drivers of agent quality improvement, providing clear signals on where to invest.
• Architect and implement reusable agent infrastructure, including multi-turn conversation workflows, recommendation services, and standardized agent topology patterns.
• Build and scale RAG pipelines and retrieval infrastructure, including vector store management and retrieval quality optimization.
• Contribute to production AI systems with a strong focus on reliability, observability, and performance.
• Partner with engineering leads and managers to inform technical direction on agent quality and evaluation strategy.
• Raise the AI engineering bar across the broader team through code review, documentation, and thoughtful technical debate.

What We Are Looking For

• 5+ years of professional software engineering experience with significant time spent on production AI/ML systems.
• Deep hands-on experience with LLM-based systems, including prompt engineering, RAG pipelines, agent orchestration, evaluation metrics, and model fine-tuning.
• Proven ability to work with data and understand statistics, especially in experiments.
• Proven ability to build and operate agentic AI systems in production, including multi-step workflows and multi-agent topologies.
• Strong command of AI evaluation, including building evaluation frameworks and understanding the difference between good and vanity metrics.
• Production-grade Python engineering skills, with a focus on clean, maintainable, and testable code.
• Experience with LangGraph or comparable agent orchestration frameworks.
• Familiarity with LangSmith or comparable LLM observability tooling for tracing, evaluation, and debugging.

Nice to Have

• Experience with large-scale AI deployments and cloud infrastructure.
• Knowledge of containerization and orchestration tools, such as Docker and Kubernetes.
• Familiarity with agile development methodologies and version control systems, such as Git.
• Experience with machine learning frameworks, including TensorFlow or PyTorch.

Benefits and Perks

• Competitive compensation package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.
• Flexible working hours and remote work options.
• Access to cutting-edge technologies and tools.
• Comprehensive health insurance and benefits package.
• Generous paid time off and vacation policy.
• Employee recognition and rewards programs.
• Professional development and training opportunities.

• Develop a strong portfolio showcasing your experience with AI and machine learning systems, including any personal projects or contributions to open-source repositories.
• Familiarize yourself with Lattice's products and services, and be prepared to discuss how your skills and experience align with the company's goals and mission.
• Practice explaining complex technical concepts in simple terms, as this will be an essential skill in this role.
• Research the company culture and values, and be prepared to discuss how you can contribute to and thrive in a collaborative and dynamic environment.
• Highlight your experience with agile development methodologies, version control systems, and containerization tools, as these are highly valued in this role.
• Be prepared to discuss your approach to AI evaluation and metrics, including how you measure success and identify areas for improvement.