• Design, develop, and maintain full-stack features across backend services, APIs, frontend, and database layers • Work primarily on backend systems (~80%) with some frontend responsibilities (~20%) • Contribute to and modernize legacy VB.NET MVC applications while supporting the migration to .NET Core • Build and integrate AI-assisted development workflows using tools such as ChatGPT, Claude, or similar technologies • Collaborate directly with clients to gather requirements, deliver enhancements, and provide technical solutions • Write and optimize SQL queries, stored procedures, and database interactions in SQL Server • Participate in Agile development processes using tools like JIRA and Git/TFS

• 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.

• Analyzing high level customer requirements and deriving lower-level functional requirements • Software development tasks including detailed software design, coding, and testing of customer desired features/user stories • Briefing software designs and demonstrating software release functionality to users • Develop and sustain new and existing applications; troubleshoot and resolve various software issues • Contribute to the creation of new distributed components and interactions that align with the future system architecture

• Design and implement highly scalable backend services, data pipelines, and integration endpoints that perform reliably at high volume. • Gather product and engineering requirements; write design documents and drive technical discussions to align cross-functional stakeholders. • Drive and lead the full software development lifecycle: product requirements, architecture, solution design, development, quality assurance, and maintenance. • Build systems with observability as a first-class concern proper monitoring, alerting, and dashboards so issues are caught before customers notice. • Mentor others on best practices and effectively share knowledge across the engineering team. • Communicate development progress clearly to product leads, engineering managers, and other stakeholders. • Be comfortable introducing new technologies and new ideas as required, including AI tools that accelerate your workflow and the team’s. • Navigate ambiguity and roadblocks proactively when a project hits a wall, you find a path forward and maintain cadence. • Work effectively as part of a large global team, attending scrum ceremonies, team events, and manager 1:1s. • Provide and respond to technical and behavioral feedback from managers and peers in written and verbal form.