As a Lead AI Engineer at InteractiveAI, you’ll operate as the Chief of AI’s right hand, driving the technical direction of our AI stack, accelerating new use cases, and guiding the development of advanced GenAI capabilities across the platform.
You’ll take ownership of the design, development, and deployment of cutting‑edge models, agentic architectures, and fine‑tuning workflows. You will lead experimentation efforts, influence architecture decisions, mentor engineers, and ensure our AI systems are scalable, reliable, and aligned with enterprise requirements.
You’ll work in a cross‑functional squad while also contributing to org‑wide AI standards, frameworks, and best practices.
Build and maintain scalable pipelines for structured/unstructured data ingestion, transformation, and feature engineering
Lead the deployment of ML models and LLMs into production, ensuring performance, reliability, and traceability
Architect and oversee fine‑tuning pipelines for LLMs with versioned checkpoints, evaluation suites, and experiment tracking
Design and implement automated evaluation frameworks (A/B testing, LLM-as-judge, validation suites) and monitoring dashboards to track latency, accuracy, drift, and trigger retraining or alerts
Guide feature engineering, imputation, and transformation strategies in complex, real‑world scenarios
Implement and optimize retrieval‑augmented generation (RAG) workflows, vector search approaches, and knowledge‑grounding strategies
Lead the development of enterprise‑grade agentic workflows, tooling integrations, and agent evaluation methods
Optimize inference speed, memory usage, and cost for high‑throughput systems across the platform
Own reliability and performance of models in production, solving challenges around latency, accuracy, drift, and scaling
Collaborate with product and delivery teams to ship client‑ready, measurable outcomes and accelerate new AI‑driven features
What We’re Looking For
We’re looking for a top-tier AI engineer with strong foundations, proven delivery, and the leadership abilities required to build production‑ready, enterprise‑grade AI systems. You should be equally capable of executing hands‑on and guiding the strategic evolution of our platform.
Minimum Requirements
5+ years in data engineering, ML engineering, applied AI, or similar deep technical roles
Experience deploying ML models and LLMs to production at scale, with strong inference optimization skills
Hands‑on experience with agent orchestration tools (LangGraph, LlamaIndex, or similar)
Experience training deep‑learning models and fine‑tuning LLMs using modern frameworks
Fluent in Python and experienced with at least one major deep learning library (PyTorch, TensorFlow, JAX, etc.)
Strong experience building production‑grade data pipelines (batch or streaming) using tools like Airflow, Spark, Dagster
Solid understanding of ML theory (bias‑variance tradeoff, probability, metrics, optimization, evaluation, etc.)
Comfortable with cloud platforms (AWS, GCP, Azure) and containerized deployments
Excellent communication skills with proven ability to mentor engineers or lead technical workstreams
Additional Requirements
Experience with LLMs and RAG pipelines in production environments
Familiarity with vector databases, embeddings, and document retrieval strategies
Exposure to MLOps practices: model monitoring, reproducibility, CI/CD for ML, automated evaluations
Experience optimizing inference latency, throughput, and cost at scale
Experience working in regulated or enterprise environments (e.g., banking, insurance)
Bonus: prior experience in technical leadership roles, architecture ownership, or acting as a technical right‑hand to a CTO/Chief of AI
What You’ll Get
Competitive base salary (from €110,000/yr to €130,000/yr) + performance bonuses
Access to equity/share plan as it rolls out.
Health & wellness allowances
Private health insurance
Flexible work setup + travel when needed (ideally Hybrid in Lisbon or Madrid)
25 days of holidays/paid time off (excluding local public holidays)
Who You Are
Proactive & Vision-Driven: You anticipate challenges, propose solutions, and help shape the future of our AI stack.
High-Ownership Leader: You move with accountability, take responsibility for outcomes, and raise the engineering bar.
Entrepreneurial & Adaptive: You thrive in ambiguity, operate with speed, and deliver in a high‑paced startup setting.
Collaborative Mentor: You work across disciplines, guide others, and contribute to a culture of high performance.
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