Mid AI Engineer
hace 3 días
Barcelona
ph3About Valeria /h3 pValeria is building the future of HR and payroll in Spain. We're an AI‑native platform that automates contracts, payroll, and compliance for companies with high employee turnover (hospitality, delivery, events, agriculture). We're rethinking how an entire industry works—moving from manual, error‑prone processes to intelligent automation. We're a fast‑growing startup backed by top investors, disrupting a €5B+ industry that is still stuck in spreadsheets and legacy software. /p h3Your Role /h3 pYou will work closely with the AI Lead, designing product AI features and transforming internal processes with AI—helping build a cross‑functional AI team with impact across every department. You’ll be a core member of our AI team, building the agents that power Valeria in production—talking to real customers and handling real payroll and legal processes. You’ll own AI features end‑to‑end: designing agent architectures, engineering context, building evals that hold up, and shipping reliable systems into a domain where correctness genuinely matters. /p ul liPrototype the complex: build proofs of concept that solve hard problems in innovative ways, then take them to production /li liTranslate business into AI: understand the business problem deeply and land it into a solid technical solution /li liDesign agents end‑to‑end: multi‑agent architectures, tools, tool‑calling, function calling, memory, orchestration, and state management /li liMaster context engineering: decide what goes into the context window and how (system prompts, few‑shot, retrieval, memory, compaction, token management), understanding why behavior changes and anticipating failure modes (hallucinations, edge cases, prompt injection) /li liBuild the LLM harness: the layer around the model—tool interfaces, output parsing and validation, retries, fallbacks, guardrails, scaffolding, and flow control that turns a model into a reliable production agent /li liEnsure reliability: solid evals and observability (datasets, metrics, regressions, production tracing) before every release—never on a single happy‑path /li liBuild high‑quality RAG systems: embeddings, vector stores, chunking, retrieval, re‑ranking, and grounding in a compliance‑heavy context /li liPick the right model: integrate and compare GPT, Gemini, and Claude, reasoning about cost, latency, reliability, context window, and fallback /li liIntegrate systems: build MCP servers and integrations with external systems /li liShip production code: solid Python, APIs, tests, CI/CD, and the team’s best practices /li liStay on the frontier: keep up with the latest models and technologies and test them to spot opportunities /li liOwn features end‑to‑end: from technical design to deployment, monitoring, and iteration based on customer feedback /li liMentor interns and evangelize AI across other departments as we scale the team /li /ul h3Required /h3 ul li3+ years of professional software engineering experience building production systems /li liStrong Python skills and solid backend fundamentals (APIs, SQL, Git, testing) /li liHands‑on experience with LLMs / agents in production: LangChain/LangGraph, RAG, prompting, tool‑calling, or equivalents /li liContext engineering and evaluation mindset: you reason about why models behave the way they do, and you validate with evals instead of a single test /li liAbility to design and break down medium‑complexity solutions autonomously, communicating progress, blockers, and trade‑offs clearly /li liStartup mindset: comfortable with ambiguity, high autonomy, and fast iteration cycles /li liStrong communication skills and ability to collaborate across product, design, and business teams /li liFluent in English and/or Spanish /li /ul h3Highly Valued /h3 ul liCloud experience: Azure (Azure OpenAI / AI Foundry) and GCP (Vertex AI / Gemini) /li liHands‑on practice / familiarity with AI coding tools such as Claude Code, Cursor, Codex, and similar /li liReact and basic frontend notions for full‑stack contributions /li liExperience deploying agents/models in production at scale /li liMCP, advanced function calling, and evaluation frameworks (LangSmith, RAGAS, or similar) /li liFine‑tuning / model optimization techniques /li liBackground in FinTech, HR‑tech, or regulated industries (compliance‑heavy products, government integrations) /li /ul h3What makes you a great fit /h3 pYou’re the kind of engineer who treats LLMs as systems to be understood, not black boxes to be prompted once. You care about reliability, you anticipate how agents fail, and you build the harness and evals that keep them honest in production. You’re pragmatic but principled, comfortable moving fast in a startup, and excited to work in a domain where correctness matters—getting payroll wrong affects real people’s lives. Bonus points if you love being on the frontier of applied AI. /p h3Our Stack /h3 ul liLanguage: Python, async APIs, SQL, Git /li liAI frameworks: LangChain / LangGraph /li liLLMs agents: prompting, context engineering, agent harness/scaffolding, tool‑calling, multi‑step agents, RAG, embeddings, vector databases /li liModels Cloud: Azure OpenAI, Gemini (GCP), Claude /li liQuality Observability: evals, testing, LLM tracing (Datadog) /li liChannel: WhatsApp API /li /ul h3Our Technical Philosophy /h3 pAs an AI‑native product, we build intelligence into every layer—automating altas, bajas, payroll, and compliance through agents that run in production, not demos. We care about reliable, testable systems over framework magic, and we treat evals and observability as first‑class. If you're excited about applying AI to solve real business problems (not building AI for AI's sake), you’ll love working here. /p h3What We Offer /h3 ul liCompetitive compensation: €40.000 - €45.000 gross salary + Equity /li liFree lunch when you’re at the office thanks to Kombo Nora /li liFlexible remuneration with Coverflex /li liFlexibility: Hybrid setup (HQ in Barcelona), 60 days/year remote work from anywhere /li liUnlimited vacation days — take the time you need, no counting days /li /ul h3Our Hiring Process /h3 ul liIntro call with People (30 min) /li liInterview with the Hiring Manager (45 min) /li liTech Assessment - Onsite at the office (1 hour) /li liFounders interview (45 min) /li liOffer /li /ul h3Why Join Valeria Now /h3 ul liTiming: We're past the "idea stage" with real customers and revenue, but early enough that you’ll define how we scale our AI /li liMarket opportunity: €5B+ market in Spain, every company with employees needs payroll, and current solutions are outdated and painful /li liReal AI ownership: you won’t assist on AI projects—you’ll build them, decide on them, and see their impact on thousands of people /li liCareer growth: be a critical AI hire, build the playbook, and grow as we scale the team /li /ul /p #J-18808-Ljbffr