AI Architect

AI Architect

Requirements

• 7+ years of experience in software leadership or enterprise architecture, including 5+ years in machine learning or AI architecture roles.
• Proven track record of shipping various flavors of AI/ML solutions – Agentic AI, Generative AI, Predictive AI, and Analytics – to production.
• Strong understanding of NLP fundamentals, including tokenization, word embeddings, language modeling, sequence labeling, and text generation.
• Deep understanding of data modeling, feedback analytics, and system integrations architecture.

Responsibilities

• Shape and execute the vision for embedding AI across Alchemer’s platform—especially in areas like natural language processing, generative AI, and feedback analytics.
• Lead the architectural strategy for Alchemer’s data and AI systems, ensuring alignment with long-term business goals and platform evolution.
• Champion responsible and ethical AI practices, including bias mitigation, transparency, data governance, and regulatory compliance.
• Architect and deploy scalable data pipelines and AI systems to analyze structured and unstructured customer feedback at scale.
• Build cloud-native AI/ML solutions, with a focus on NLP, LLM-based systems, and generative AI (AWS preferred).
• Translate business strategy into practical AI architectures, roadmaps, and delivery plans.
• Lead solution design across the AI lifecycle: model training, deployment, monitoring, performance tuning, and continuous improvement.
• Write clean, maintainable code in Python, ensuring functionality and performance.
• Deliver robust, production-grade systems that can handle real-time, and batch processing demands.
• Work hand-in-hand with Product, Engineering, and Data teams to ensure seamless integration of AI into existing platform capabilities.
• Build AI features that surface insights to non-technical users—empowering frontline agents and decision-makers.
• Create data architectures that unify feedback signals across diverse SaaS systems and customer touchpoints.
• Conduct technical assessments, feasibility studies, and POCs to rapidly test and validate new capabilities.
• Mentor engineers and data scientists on AI/ML best practices, model reliability, and production readiness.
• Present AI architecture and roadmaps to internal stakeholders and executive leadership.
• Support hiring and team planning efforts as we scale AI capabilities across the company.
• Drive thought leadership initiatives, including internal upskilling and AI community engagement within Alchemer.

Preferred Qualifications

• Experience with modern AI/ML data and Lakehouse platforms such as: Databricks, AWS SageMaker, Glue, Azure ML, Vertex AI, or Dataiku
• Snowflake, Redshift, BigQuery, Azure Data Warehouse, Fivetran
• Experience with designing compelling insights using BI tools: Thoughtspot, Tableau, PowerBI
• Exceptional efficiency in AI/ML programming such as Python, R, PyTorch, TensorFlow, scikit-learn, LangChain
• Advanced knowledge of SQL, NoSQL, Graph databases – Cassandra, MongoDB, Dynamo, MySQL, PostgresSQL
• Experience with data processing – Kafka, Druid, Elastic, PySpark , Apache Spark – data embedding using LLMs, Vector databases and prompt engineering
• Familiarity with DevOps and MLOps: Git, CI/CD pipelines, IaC, containerization.
• Experience navigating regulated environments (HIPAA, GDPR, etc.) is a plus.
• Formal degree (BS or MS) in statistics, mathematics, computer science or related technical field