Senior AI Engineer
About SubcontractorHubWe are bringing order to the chaos of the home services industry. SubcontractorHub is a comprehensive, AI-powered operating system tailored for contractors in Solar, Roofing, and HVAC. By centralizing leads, contracts, project management, and finances, we eliminate administrative bottlenecks and help contractors save time, reduce costs, and scale efficiently.Our mission is to empower home service professionals to focus on growth rather than paperwork. AI is at the core of how we deliver that efficiency—and we are looking for the right engineering leader to help us push the boundaries of what our platform can do.The RoleWe are seeking an exceptional Senior AI Engineer who can bridge the gap between applied research and robust production systems. In this role, you won't just be tweaking models or building local demos; you will own end-to-end AI capabilities that our customers rely on every day.Working closely with our AI Research team in Sofia, you will take their modeling patterns and research artifacts and apply the operational rigor needed to ship them as highly reliable, customer-facing features. You will set the standard for our AI organization through the quality of your code, your evaluation rigor, and your commitment to system safety.What You'll DoEnd-to-End Ownership: Take AI features from problem framing and research prototypes through productization and post-launch monitoring.Build Agentic Workflows: Develop and orchestrate advanced multi-agent systems and LLM-based applications using LangGraph and Python.Model Development: Train, fine-tune, and evaluate models using PyTorch and Hugging Face (leveraging LoRA and PEFT techniques where appropriate).Design Rigorous Evaluations: Build the evaluation harness alongside the feature. Handle dataset curation, define metrics, utilize LLM-as-judge approaches, and analyze agent trajectories.Ensure Production Safety: Implement strict operational guardrails for a multi-tenant SaaS environment, including prompt injection defenses, PII handling, output validation, jailbreak prevention, and circuit breakers for agent loops.Technical Leadership & Communication: Raise the engineering bar by writing clear, precise PR descriptions, technical proposals, and architecture notes that a distributed team can rely on.Tech StackBackend API: Python, FastAPI, Pydantic, SQLModelAI & Agents: LangGraph, LangChain, Pydantic AIML & Model Dev: PyTorch, Hugging Face, scikit-learn, XGBoost, NeuralProphetData Processing: Polars, Pandas, DatabricksPDF & Browser Automation: PyPDF, PyPDFium2, PyMuPDF, PlaywrightDatabases & Cache: PostgreSQL, MariaDB, ValkeyObservability: Logfire, Sentry, DatadogWhat We Are Looking ForProven Production Experience: 5+ years of hands-on applied AI/ML experience. You have shipped systems with real users behind them, not just research papers or personal projects.Agentic Expertise: Deep familiarity with prompt design, tool use, Retrieval-Augmented Generation (RAG), memory architectures, and the specific failure modes that only appear at scale.Applied Fine-Tuning Discipline: You possess the practical knowledge to curate datasets and design evaluations, coupled with the discipline to know exactly when fine-tuning is necessary versus when prompting or RAG is the right tool.Data Fluency: You are comfortable writing SQL against large relational databases, building data pipelines, and extracting clear training signals from messy production data.Strong CS Foundation: Advanced proficiency in Software Development, Pattern Recognition, and Neural Networks.Education: Master's or higher degree in Computer Science, AI, or a related field (or equivalent practical experience).Bonus PointsComputer Vision: Experience with image segmentation, object detection, or polygon extraction is a strong advantage.Domain Experience: Previous experience developing AI applications for B2B SaaS, business management platforms, or the construction/contractor industry.