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Lattice is a people success platform that empowers leaders to build engaged, high-performing teams & winning cultures.
Senior Software Engineer, AI
Location
United States
Posted
87 days ago
Salary
$135.5K - $169.5K / year
Seniority
Senior
Job Description
Senior Software Engineer, AI
Lattice
• Design and ship a robust, end-to-end AI evaluation framework, covering offline evals, production tracing, and human-in-the-loop feedback loops, connected across all of Lattice’s AI use cases. • Define and instrument the metrics that actually matter: 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 the drivers of agent quality improvement, giving the team clear signals on where to invest. • Architect and implement reusable agent infrastructure: multi-turn conversation workflows, recommendation services, LLM DAGs, and standardized agent topology patterns using LangGraph. • Build and scale RAG pipelines and retrieval infrastructure, including vector store management and retrieval quality optimization. • Make principled build vs. buy decisions across LLM providers, agent frameworks, and evaluation tooling, balancing capability, cost, latency, and vendor risk. • Contribute to production AI systems with a strong focus on reliability, observability, and performance, not just prototypes. • Own projects end-to-end: scope them, drive them to completion, and bring in the right people at the right time. • Partner with engineering leads and managers to inform technical direction on agent quality and evaluation strategy you’ll be expected to hold intelligent, substantive conversations about methodology, not just implementation. • Raise the AI engineering bar across the broader team through code review, documentation, and thoughtful technical debate.
Job Requirements
- 5+ years of professional software engineering experience with significant time spent on production AI/ML systems.
- Deep hands-on experience with LLM-based systems: 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: multi-step workflows, multi-agent topologies, and the failure modes that come with them.
- Strong command of AI evaluation: you’ve built eval frameworks before, you know the difference between a good eval and a vanity metric, and you have opinions about it.
- Production-grade Python engineering: clean, maintainable, testable code.
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Life, AD&D, and Disability Insurance
- Emergency Weather Support
- Wellness Apps
- Paid Parental Leave
- Paid Time off inclusive of holidays and sick time
- Commuter & Parking Accounts
- Lunches in the Office
- Internet and Phone Stipend
- 401(k) retirement plan
- Financial Planning
- Learning & Development Budget
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