AI Architect
Estonia, Tallinn
Pipedrive
Pipedrive is the easy-to-use, #1 user-rated CRM tool. Get more qualified leads and grow your business with our sales CRM. Sign up for a 14-day free trial.Be the curator and owner of the AI architecture strategy in Pipedrive. Act as the glue between data scientists, data engineers, developers, operations (DevOps, DataOps, MLOps), and business unit leaders to govern and scale the AI initiatives within Pipedrive that drive business value. Serve as a trusted advisor, both practical and innovative, to embed innovative data/ai/ml solutions into existing business areas and transform data into strategic assets.
Your new adventure:
- AI/ML Architecture
- Design scalable and secure AI/ML infrastructure for both cloud and on-premises environments.
- Architect modular Generative AI solutions, including LLM-based APIs, embedding pipelines, vector search, and RAG architectures.
- Select appropriate AI/ML techniques (e.g., NLP, computer vision, reinforcement learning) based on business needs and use cases.
- Data & AI Integration
- Define AI architecture in alignment with the organization’s data and product strategy.
- Collaborate with data engineers to design robust, secure, and high-quality data pipelines for AI use cases.
- Ensure seamless data integration, access control, and data quality for training and inference both in batch and real-time.
- GenAI/LLM Strategy
- Define reference architectures and standards for GenAI and LLM adoption across the enterprise.
- Lead the design of RAG systems, leveraging vector databases and structured/unstructured knowledge sources.
- Evaluate LLM deployment options (e.g., commercial APIs, on-prem models, open-source fine-tuned models) based on latency, cost, compliance, and privacy.
- Technology Strategy
- Develop an AI strategy and architectural roadmap aligned with business objectives.
- Stay ahead of emerging AI trends and evaluate new tools, frameworks, and platforms (e.g., PyTorch, TensorFlow, Kubernetes, Docker).
- Provide technical leadership across platform, product, and support functions.
- Cross-functional Collaboration
- Collaborate closely with product managers, engineers, and data scientists to integrate AI into user-facing and internal products.
- Communicate AI capabilities and decisions clearly to technical and non-technical stakeholders.
- Governance, Security & Ethics
- Ensure AI systems comply with privacy, security, and ethical standards (e.g., GDPR, AI ethics guidelines).
- Help define and implement responsible AI governance frameworks across the lifecycle of AI systems.
Does this sound like you?
- Experience:
- 5+ years in AI/ML development with experience in architecting AI solutions.
- Proven track record of designing and deploying AI/ML models in production environments.
- Technical Skills:
- Strong expertise in machine learning algorithms, deep learning, and statistical models.
- Proficiency with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Deep understanding with cloud AI/ML services (e.g., AWS SageMaker, Azure ML, GCP AI).
- Experience with data pipeline tools (e.g., Apache Kafka, Airflow) and containerization (Docker, Kubernetes).
- Knowledge of programming languages such as Python, R, and Java.
- Knowledge of big data processing frameworks (e.g., Hadoop, Spark).
- Proficiency in GenAI offerings and approach for driving adoption internally and within the product.
- Expertise in architecting and scaling GenAI solutions, including:
- LLM orchestration tools (e.g., LangChain, Haystack)
- Vector databases (e.g., Pinecone, Weaviate, FAISS)
- RAG pipelines
- Experience with design patterns for GenAI systems, such as agent frameworks, tool calling, memory, and contextual window management.
- Proficient in designing systems that address LLM cost optimization, latency, rate-limiting, and failover in production environments.
- Familiarity with LLM evaluation frameworks (e.g., TruthfulQA, HELM) and AI safety techniques (guardrails, moderation APIs, response validation).
- Implement architectural controls for prompt injection resistance, logging, and observability for audit and risk tracking.
- Soft Skills:
- Thought leadership
- Strong problem-solving skills and ability to lead complex AI projects.
- Excellent communication and leadership skills.
- Ability to work in a fast-paced, collaborative environment.
- Education:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Ph.D. is a plus.
Why Pipedrive:
- People-first culture - Be part of a team that values authenticity, champions collaboration, and supports each other—no egos, just teamwork. Work alongside top talent from around the world in an inclusive space where different perspectives fuel our best ideas. Everyone is welcome
- Unlock potential – Push boundaries, take ownership, and experiment with the latest technologies as we enhance our AI First Vision. We empower bold ideas that drive real change
- We’ve got you – Your well-being matters. Enjoy flexible hours, wellness perks and SWAG. Think performance-based bonuses, 28 paid leave days, well-being days, compassionate leave, and even pawternal leave—because we take care of ourselves and our people
- Grow with us – Whether through mentorship, coaching, or internal mobility, we invest in helping you unlock your potential. Open, honest feedback and clear communication are at our core. We grow together through trust and accountability
- Packed with purpose – Help 100,000+ small and medium-sized businesses grow and succeed while doing meaningful, customer-driven work
Based on this role's access to certain data, Pipedrive might conduct a pre-employment background investigation in conjunction with your application for employment with our company. Such data will be handled in accordance with Pipedrive's Privacy Policy for Recruitment.
Pipedrive is an equal opportunity employer. We encourage diversity in the workplace regardless of age, gender, race, religion, disability, sexual orientation, gender identity or veteran status.
Please note that for this role we’re currently unable to offer relocation assistance or visa sponsorship.
#LI-Hybrid #LI-VMUC
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AI governance Airflow AI strategy APIs Architecture AWS Azure Big Data Computer Science Computer Vision DataOps Data pipelines Data quality Deep Learning DevOps Docker FAISS GCP Generative AI Hadoop Haystack Helm Java Kafka Kubernetes LangChain LLMs Machine Learning ML infrastructure ML models MLOps NLP Open Source Pinecone Pipelines Privacy Python PyTorch R RAG Reinforcement Learning Responsible AI SageMaker Scikit-learn Security Spark Statistics TensorFlow Weaviate
Perks/benefits: Career development Equity / stock options Flex hours Relocation support Salary bonus Wellness
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