AI ML Engineer

📋 Description

• • Architect, build, and harden AI/ML solutions that move the needle for 1,800+ BPM professionals across Tax, Assurance, Advisory, and Corporate Services. You will own the full lifecycle—from ideation and data wrangling to model training, deployment, and continuous monitoring—ensuring every algorithm translates into measurable time savings, higher accuracy, and new revenue opportunities.
• • Rapidly prototype and productionize AI features such as domain-specific chatbots, Copilot extensions, and intelligent workflow automations that eliminate repetitive tasks and free our professionals to focus on high-value client work. Expect to ship MVPs in weeks, iterate with real user feedback, and scale the winners to thousands of daily active users.
• • Establish robust data pipelines that ingest, cleanse, and label structured and unstructured data from internal systems (e.g., CCH Axcess, Thomson Reuters, NetDocuments) while enforcing strict security, privacy, and ethical AI standards. You will define data contracts, implement versioning, and create automated quality checks that keep models honest and compliant.
• • Embed AI natively into the Microsoft ecosystem—Azure OpenAI, Copilot Studio, Power Platform, Teams, and SharePoint—so colleagues can interact with models in the tools they already use. You will design low-friction UX, single-sign-on flows, and role-based access controls that delight users and satisfy auditors.
• • Partner with cross-functional squads of tax managers, auditors, consultants, and IT engineers to uncover pain points ripe for AI intervention. You will translate complex regulatory and business requirements into crisp technical specs, run design-thinking workshops, and present ROI dashboards that secure ongoing executive sponsorship.
• • Champion responsible AI by implementing explainability layers, bias detection, and fairness audits. You will author governance playbooks, lead lunch-and-learns, and sit on the AI Ethics Council to ensure every model we ship meets BPM’s risk appetite and regulatory obligations.
• • Shape the culture, tooling, and delivery rituals of BPM’s newly formed AI Engineering team. You will evaluate MLOps stacks, set coding standards, mentor junior data scientists, and create reusable templates that accelerate future projects across the firm.
• • Stay on the bleeding edge—experiment with emerging frameworks like LangChain, vector databases, and MCP (Model Context Protocol), then distill your findings into concise briefs that guide strategic investment decisions. Your research will directly influence BPM’s three-year AI roadmap.
• • Measure what matters: define KPIs (e.g., hours saved, error-rate reduction, user NPS), instrument telemetry, and publish monthly impact reports to leadership. You will A/B test features, tune models in production, and sunset underperformers with surgical precision.
• • Foster a feedback-rich environment by hosting office hours, writing internal blogs, and recording bite-sized training videos. Your ability to demystify AI for non-technical stakeholders will be the catalyst for firm-wide adoption and cultural transformation.