Forward-Deployed AI Engineer

Job Title: Forward-Deployed AI Engineer Company: Bottomline Job Category: Machine Learning Roles & Responsibilities: The Role We're looking for an Forward\-Deployed AI Engineer (FDE) who can take a business problem and solve it natively in Snowflake — from feature engineering through model training to deployment as a live service. This is not a platform\-building role. You won't be designing schemas or managing pipelines. You'll be the person who turns business questions into working AI solutions that run in production. What You Will Do * Take business problems (e.g. churn risk, propensity to buy, anomaly detection, document intelligence) and design AI solutions using Snowflake\-native capabilities * Build and evaluate ML models using Snowflake ML Functions, Snowpark ML, and Cortex AI * Design and implement Cortex Agents that combine structured data queries with unstructured document intelligence * Create evaluation frameworks (golden datasets, LLM\-as\-judge, human review loops) to prove solutions meet success metrics * Work with Cortex Analyst semantic views to enable natural language access to business data * Build Cortex Search services over unstructured documents (contracts, support tickets, product docs etc.) * Collaborate with AI and Data Engineers who handles platform infrastructure, you focus on the science, they handle the plumbing * Present findings and recommendations to business stakeholders in plain language * Contribute to the AI project lifecycle: framing problems, running spikes, evaluating results, and iterating Why This Role Is Different * AI\-native, not AI\-assisted: You will build solutions where the AI IS the product, not a feature bolted onto something else * No ML infrastructure tax: Everything runs natively in Snowflake — no Docker, no Kubernetes, no model serving endpoints to manage * You will have business impact from day one: with a prioritised backlog of Quick Win candidates waiting for someone to build them * Direct line to stakeholders: No layers of middle management between you and the business problem. * Modern AI engineering practices: Lifecycle\-governed (Framing \> Spikes \> Build \> Evaluate \> Governance \> Adoption), evaluation\-driven, with a real governance plane Work Location: Greater Bengaluru Area Availability: Full time

Requirements : Must Have * 3\-0-1 years of experience in data science, machine learning, or applied AI * Strong Python (pandas, scikit\-learn, numpy), you think in DataFrames * SQL fluency, comfortable writing complex analytical queries, window functions, CTEs * Experience building classification or regression models and evaluating them rigorously (precision, recall, F1, AUC) * Experience with at least one of: NLP, document extraction, recommendation systems, or anomaly detection * Comfortable working with messy real\-world data — missing values, inconsistent formats, multiple sources * Great communications skills and can work directly with stakeholders end to end * Can communicate findings to non\-technical stakeholders clearly * Snowflake experience (Snowpark Python, Cortex AI functions, ML model registry) * Experience with LLMs in production (prompt engineering, RAG architectures, evaluation of generative outputs) * Understanding of Cortex Agents, Cortex Search, or Cortex Analyst * Experience building evaluation sets and measuring AI quality systematically (not just accuracy, precision/recall tradeoffs, error analysis) * Familiarity with feature engineering for tabular business data (customer signals, transaction patterns, contract attributes etc) * Experience in Fintech, B2B payments, or B2B SaaS * Familiarity with A/B testing or causal inference methods * Experience with Streamlit for rapid prototyping of data apps Key Skills: Machine Learning, Python, Pandas, NumPy, Model Training, Feature Engineering, NLP Salary: Not disclosed