Lead AI Engineer

• 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

• 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

• 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

• Competitive base salary (from 110000/yr to 130000/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)

• 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.

1. Intro Call 30 minutes with our team to align on fit and expectations
2. Take-Home Challenge A practical task based on real-world problems
3. Technical Interview Deep dive into the challenge technical experience and AI engineering
4. Cultural and Values Interview Discussion on motivation cultural and value alignment
5. Offer Final conversation and offer

InteractiveAI is a fast-growing startup on a mission to empower enterprises with fully managed AI agent lifecycles.
We are building the next generation of enterprise-AI solutions delivering an end-to-end Agentic IDE alongside an extensible ecosystem of agentic resources and solutions.

Our platform allows companies to orchestrate monitor evaluate deploy and improve AI agentsand soon fine-tune and own their own models.

We value autonomy speed and innovation and were building a world-class team to match. Our squads are lean focused and execution-driven.

If you thrive in high-performance environments and want to be part of a company that rewards transformational outcomes this is for you.