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EPAM Systems
AI practice lead - Financial services and Insurance
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What they do
An Artificial Intelligence Engineer develops, tests, and deploys artificial intelligence models. May work closely with data software engineers and data professionals to train and implement AI models into existing systems or develop new applications.
$125,739 / year median in the U.S.
Job Description
We are seeking an AI leader to drive innovation and delivery across our Financial Services and Insurance portfolio. You'll oversee the full lifecycle of AI solutions, from ideation to production, shaping strategy, leading multidisciplinary teams, and building new capabilities in a fast-evolving market. EPAM is where tech talent thrives—building groundbreaking solutions, advancing your skills through world-class learning platforms, and working alongside a global community of problem-solvers to make the future real. Req# 1060146090
- Responsibilities
- + Work with clients and internal teams to shape the AI, machine learning, and agentic business and technology vision and go-to-market offerings + Manage end-to-end data science, artificial intelligence, and agentic projects and programs + Lead multidisciplinary workshops and design sessions with customers + Develop high-quality proposals in collaboration with subject matter experts and consultants + Contribute to the evolution of data science, artificial intelligence, and agentic offerings + Grow team capacity and capability, build new competencies, mentor team members, and champion transformation with stakeholders •Requirements•+ 10+ years of experience as a data science lead, machine learning engineering lead, or similar roles in banking, investment, underwriting, actuarial, or consulting for financial services, insurance, or reinsurance + 5+ years in a leadership role with team management responsibilities + Strong communication skills with the ability to explain complex concepts to diverse audiences + Hands-on experience in at least one domain: computer vision, natural language processing, recommender systems, or time series analytics + Machine learning engineering and production delivery experience, including ML/LLMOps and cloud platforms + Knowledge of technologies such as Databricks, Snowflake, or agentic orchestration tools (LangChain, Omnigent, Semantic Kernel) + Working knowledge of at least one programming language, ideally Python + Understanding of data science engineering excellence and the modern software development lifecycle for artificial intelligence products + Consulting experience in a professional services environment •Nice to have•+ Current AI leadership experience in a financial services or insurance organization + Referenceable work such as papers, open-source contributions, or conference talks in the AI or machine learning space + Current cloud certifications for Amazon Web Services, Google Cloud Platform, Microsoft Azure, or Databricks + Experience with regulatory processes and standards such as KYC/AML, ISO/IEC, FSB, IFRS, or FINTRAC •We offer•+ Medical, Dental and Vision Insurance (Subsidized) + Health Savings Account + Flexible Spending Accounts (Healthcare, Dependent Care, Commuter) + Short-Term and Long-Term Disability (Company Provided) + Life and AD&D Insurance (Company Provided) + Employee Assistance Program + Unlimited access to LinkedIn learning solutions + Matched 401(k) Retirement Savings Plan + Paid Time Off - the employee will be eligible to accrue 15-25 paid days, depending on specific level and tenure with EPAM (accrual eligibility may change over time) + Paid Holidays - nine (9) total per year + Legal Plan and Identity Theft Protection + Accident Insurance + Employee Discounts + Pet Insurance + Employee Stock Purchase Program + If otherwise eligible, participation in the discretionary annual bonus program + If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program •This Remote Position Cannot be Performed in New York City.
- This posting includes a good faith range of the salary EPAM would reasonably expect to pay the selected candidate.