Forward-Deployed AI Engineer

Why Choose Bottomline? Are you ready to transform the way businesses pay and get paid? Bottomline is a global leader in business payments and cash management, with over 35 years of experience and moving more than $16 trillion in payments annually. We're looking for passionate individuals to join our team and help drive impactful results for our customers. If you're dedicated to delighting customers and promoting growth and innovation - we want you on our team! Job Description: Forward-Deployed AI Engineer     Location   India (Pune / Bangalore / Remote India)   Reports To   Snr. Director of AI and Data, Enterprise Data Services (UK)   Level   Individual Contributor (3-4 years experience)   Team   Enterprise Data Services — AI Engineering   Contract   Permanent, Full-Time   HRFs   BTF27272, BTF27273     About the Team   Enterprise Data Services (EDS) is Bottomline's AI Engineering function. We don't build AI as a side tool — we build AI-native solutions where intelligence IS the product. Our platform runs on Snowflake, and we use Snowflake's native AI capabilities (Cortex AI, Cortex Agents, Cortex Search, Cortex Analyst, ML Functions) to solve business problems directly in the data platform, no external ML infrastructure, no separate serving layer, no handoffs between teams.   We currently ship: churn prediction agents, contract intelligence, partner reporting automation, a governance control plane, and much more. Everything runs in Snowflake. Everything is versioned, tested, and production-governed.   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 Engineer s 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   Requirements   Must Have   3-4 years 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   Strong Preference   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 )   Nice to Have   Experience in F intech, B2B payments, or B2B SaaS   Familiarity with A/B testing or causal inference methods   Experience with Streamlit for rapid prototyping of data apps   Our Tech Stack   Snowflake (everything lives here): Cortex AI, Cortex Agents, Cortex Search, Cortex Analyst, Snowpark Python, ML Functions, Dynamic Tables   Python: pandas, scikit-learn, snowpark -ml, evaluation frameworks   Version control: Git, Snowflake stage-based deployment   Visualisation: Streamlit in Snowflake, Cortex Code (IDE) , PowerBI   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 b usiness 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   Your First 90 Days   Days 1-30: Learn   Understand the Snowflake platform and Cortex AI capabilities   Run through the AI project lifecycle on a small candidate   Days 30-60: Spike   Own your first AI candidate from the prioritised backlog    Run a timeboxed spike s : build the crudest version that proves positive signal   Create your first golden evaluation dataset   Present spike findings to the team   Days 60-90: Build   Build your spike to production standard with proper evaluation   Pass through governance gates   Ship your first AI solution to production   We welcome talent at all career stages and are dedicated to understanding and supporting additional needs. We're proud to be an equal opportunity employer, committed to creating an inclusive and open environment for everyone.