Forward-Deployed AI Engineer

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

India (Pune / Bangalore / Remote India)

Snr. Director of AI and Data, Enterprise Data Services (UK)

Individual Contributor (3-4 years experience)

Enterprise Data Services — AI Engineering

Permanent, Full-Time

** HRFs**

BTF
27272, BTF
27273

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 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

Requirements

Must Have

• 3-4 years experience in data science, machine learning, or applied AI
• Strong Python (pandas, scikit-learn, numpy), you think in Data Frames
• 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…