About the RoleAs our Senior AI Engineer, you'll help execute the AI strategy for the platform - facilitating how AI is used to help financial services create, configure, and optimize their data integrations and transformations. The AI layer is what turns a capable platform into a genuinely new category of product.
You'll work with a team of AI engineers, remain deeply hands-on technically, and work closely with the Head of Engineering to ensure the AI layer integrates cleanly with the core platform. You'll help the organization take the decisions that matter - LLM selection, agentic architecture, RAG design, evaluation frameworks, and the interaction model that defines what "AI-native" actually means when applied to financial data workflows.
The challenge here is specific: AI outputs in a financial services context need to be accurate, explainable, and auditable. Generic LLM approaches are not sufficient. You'll build something that is both intelligent and trustworthy.
ResponsibilitiesAI Strategy & Architecture- Execute the AI strategy - LLM selection and management, agentic application architecture, RAG system design, prompt engineering standards, and evaluation frameworks
- Help design and implement the core AI capabilities: transformation generation from natural language, integration configuration assistance, data quality detection, and intelligent validation
- Determine where AI adds genuine value vs. where deterministic logic is more appropriate - this judgment is critical for a financial services product
- Set technical standards and foster a culture of experimentation grounded in production discipline
- Partner with the Head of Engineering and Head of Design on cross-functional AI feature development
Hands-On Development- Remain deeply technical - architect and implement core AI features
- Build and evolve the transformation generation engine, integration suggestion system, and intelligent validation layer
- Design the AI pipeline architecture that operates reliably inside Agno-orchestrated workflows
Model Operations- Establish evaluation, monitoring, and continuous improvement practices for production AI systems
- Build frameworks to measure AI output quality - accuracy, consistency, and user acceptance rates
- Implement production monitoring and model drift detection
Responsible AI- Define responsible AI practices appropriate for financial services - accuracy thresholds, auditability requirements, and appropriate human-in-the-loop controls
- Ensure AI outputs are explainable to both technical and non-technical users
RequirementsExperience- 3+ years AI/ML engineering; 5+ years in a product development environment
- Player-coach track record - has led teams while remaining deeply hands-on
Technical Skills- Expert Python proficiency
- Deep production LLM experience - RAG pipelines, prompt engineering, agentic systems, evaluation frameworks
- Production experience with agentic frameworks - Agno strongly preferred; LangChain, LlamaIndex, or comparable also considered
- Workflow orchestration experience (Temporal, Prefect, or Airflow) - AI components must operate reliably within platform workflows
- Azure (primary) or AWS
- Vector databases and embedding systems (Pinecone, Weaviate, pgvector, or comparable)
- Active daily user of AI coding assistants - this is a cultural requirement, not just a preference
Nice to Have- Financial services, fintech, or regulated industry background - understanding of what accuracy and auditability mean in a compliance-sensitive context
- MLOps and model deployment at scale
- Experience fine-tuning open-source LLMs for domain-specific tasks
- Publications, conference talks, or open-source AI contributions
- Experience building AI features for data tools, analytics platforms, or enterprise SaaS products
Why Join UsCategory-defining work - AI-native data integration and transformation for financial services doesn't exist yet. You'll help build it from the ground up.
Enterprise backing, startup speed - The credibility, domain expertise, and runway of an established enterprise combined with the pace of a startup. This is an unusual opportunity.
Foundational team - You'll be among the first in-house hires. You'll set architecture, culture, and standards - not inherit them.
Competitive package - Market-rate salary and comprehensive benefits. Equity is available for select roles. Poland-based team members receive private healthcare (Medicover or Luxmed), Multisport card, home office setup budget, and professional development budget.
Salary RangeMA: $210,000 - $260,000 base salary + target annual bonus
NY/NJ: $210,000 - $260,000 base salary + target annual bonus
BBH and its affiliates' compensation program includes base salary, discretionary bonuses, and profit-sharing. The anticipated base salary range(s) shown above are only for the indicated location(s) and may differ in other locations due to cost of living and labor considerations. Base salaries may vary based on factors such as skill, experience and qualification for the role. BBH's total rewards package recognizes your contributions with more than just a paycheck-providing you with benefits that enhance your experience at BBH from long-term savings, healthcare, and income protection to professional development opportunities and time off, our programs support your overall well-being.
We value diverse experiences. We value diverse experiences and transferrable skillsets. If your career hasn't followed a traditional path, includes alternative experiences, or doesn't meet every qualification or skill listed in the job description, please do go ahead and apply.
