• Own and continuously improve engineering team processes and workflows • Ensure engineers have clear, actionable priorities and deliverables • Conduct regular 1:1s, providing mentorship and supporting career development • Participate in hiring, onboarding, and team growth initiatives • Foster a culture of trust, ownership, consistency, and transparency • Help unblock engineers on technical or product-related challenges • Partner closely with Product to define roadmap priorities and ensure technical alignment • Collaborate with leaders across engineering, product, and operations • Document technical requirements and proposed solutions clearly for the team • Collaborate with cross-functional partners to translate customer needs into scalable software solutions • Build and maintain systems using technologies such as Go, CosmosDB, Postgres, Azure Functions, Event Grid, and Event Hub • Support and modernize legacy systems built in .NET/C# and SQL Server • Actively identify and reduce technical debt as part of feature development • Design and maintain complex data pipelines supporting business-critical systems (e.g., tax filing, rate ingestion, order ingestion) • Partner with Product to understand customer reporting and data needs • Establish and promote clean, consistent data standards across the organization • Work extensively with Databricks on Azure, leveraging tools such as Delta Tables, Lakeflow Declarative Pipelines, Workflows, and Unity Catalog • Promote best practices for code quality, testing, and documentation • Participate in and lead code reviews to maintain high engineering standards

• Develop and maintain full-stack applications using Next.js / React, NestJS, TypeORM, and PostgreSQL • Implement reliable, scalable APIs and data models • Contribute to front-end components and user experience improvements • Collaborate cross-functionally with product, data, and infrastructure teams • Participate in code reviews, technical discussions, and design sessions • Troubleshoot performance issues and optimize for scalability and maintainability • Document features, APIs, and workflows clearly and consistently

• Engineer production-grade prompt infrastructures for complex workflows, including candidate evaluation, resume parsing, interview automation, and autonomous stakeholder communication. • Deploy advanced prompting paradigms—including Chain-of-Thought (CoT), Tree-of-Thought, Self-Consistency, and Instruction Hierarchies—to ensure high-precision reasoning. • Architect robust guardrails and instruction-following protocols to maintain system safety, prevent jailbreaks, and ensure strict adherence to hiring rubrics. • Build and manage stateful, multi-agent workflows using LangGraph and LangChain. • Design complex, multi-step decision trees that incorporate human-in-the-loop (HITL) checkpoints, autonomous error recovery, and conditional branching. • Optimize execution paths for latency and token cost without compromising the depth of analysis or system reliability. • Architect Retrieval-Augmented Generation (RAG) pipelines that ensure high-fidelity context injection, minimizing hallucinations through rigorous source attribution. • Manage integration with vector databases (Pinecone, Weaviate, Chroma) and implement advanced retrieval strategies such as semantic re-ranking, query expansion, and context compression. • Define and implement automated evaluation frameworks (LLM-as-a-Judge) to conduct regression testing on prompts and measure output drift. • Make strategic decisions regarding model routing (GPT-4 vs. Claude vs. Gemini) and determine the viability of PEFT/LoRA fine-tuning versus context-window optimization. • Establish strict documentation standards for prompt versioning and reproducibility to ensure enterprise-grade compliance.

• Own day-to-day operations and administration of HubSpot for the marketing team. • Ensure campaign execution, data hygiene, and accurate integration with the broader martech stack • Design and manage scalable marketing infrastructure including email programs, forms, landing pages, workflows, lead scoring, and lifecycle tracking. • Ensure data quality and hygiene through proactive list management, enrichment monitoring, deduplication, and field mapping consistency. • Develop dashboards and reports to monitor key KPIs. • Partner with RevOps on attribution modeling and full-funnel reporting integrity. • Lead campaign and channel analysis, experimentation, and iteration to drive performance improvement. • Drive operational rigor by documenting SOPs, standardizing execution frameworks, and establishing repeatable processes. • Lead change management efforts for new tools, integrations, and process rollouts. • Support and optimize demand generation programs through operations with measurable impact on pipeline and revenue.