Forward-Deployed AI Engineer
Bottomline
- India
- Mid Level
- 3+ years
- Posted
Skills
Required
- AI
- data science / machine learning / applied
- Python
- pandas
- scikit-learn
- numpy
- A/B testing / causal inference methods
- Streamlit
Preferred
- Cortex
- Snowflake
- Cortex Agents / Cortex Search / Cortex Analyst
- Snowpark
- NLP / document extraction / recommendation systems / anomaly
- feature engineering
- payments
- SQL
- writing complex analytical queries
- window functions
About Bottomline
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!
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.
Responsibilities
- Reports To
- Snr. Director of AI and Data, Enterprise Data Services (UK)
- Level
- HRFs
- 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.
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.
- and Data
- 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
- 3-4 years experience in data science, machine learning, or applied AI
- Strong Python (pandas, scikit-learn, numpy
- Great communications skills and can work directly with stakeholders end to end
- intech, B2B
- Familiarity with A/B testing or causal inference methods
- Experience with Streamlit for rapid prototyping of data apps
Preferred
- 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
- 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
- precision/recall tradeoffs, error analysis)
- Familiarity with feature engineering for tabular business data (customer signals, transaction patterns, contract attributes
- payments, or B2B SaaS
Pay
Individual Contributor (3-4 years experience)
Team
Enterprise Data Services — AI Engineering
BTF27272, BTF27273
Experience building evaluation sets and measuring AI quality systematically (not just accuracy
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
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