Job description

Curinos empowers financial institutions to put customers at the center of every decision. Our AI-first platform transforms proprietary data, advanced analytics and deep financial services expertise into timely recommendations - delivered right where teams work. The result: confident decisions, stronger customer relationships, and lasting, profitable growth. Curinos operates under a hybrid modality and has office locations in New York, Chicago, Boston, Toronto, and London. This role is open to hybrid/ remote candidates based in the United States. Job Description We are seeking a Staff ML/AI Platform Engineer to help build and operate Curinos' Databricks-native AI platform. This role sits at the intersection of machine learning engineering, platform engineering, and site reliability, with a focus on enabling reliable deployment and operation of AI and ML systems at scale. This is a high-impact role that will unlock the next phase of Curinos scalable growth. You will be responsible for designing and implementing the infrastructure, tooling, automation, observability, and governance capabilities that power production machine learning models, LLM applications, and agentic AI workflows. You will help establish technical architecture and engineering standards across teams, and work with applied scientists to move solutions from experimentation to production quickly, safely, and repeatably. You will “build it once and scale it many times.” We are a Databricks-first organization and make extensive use of Databricks Workflows, Asset Bundles, Unity Catalog, MLflow, Delta Live Tables, and related ecosystem tools. You will work closely with data scientists, data engineers, software engineers, and product teams embed AI and ML capabilities into our products, as well as automate operational processes to achieve reliable, scalable efficiencies across data and algorithmic workflows company-wide. As a FinTech company operating in a regulated environment, we place strong emphasis on governance, reproducibility, observability, and operational excellence. This role is critical to ensuring our AI platform and ML solutions meet those standards while remaining fast-moving and developer-friendly. Responsibilities • Design, build, and maintain platform capabilities for deploying, monitoring, and operating ML models, LLM applications, and agentic AI workflows.providing technical direction on architecture and scalability • Develop automated CI/CD pipelines and infrastructure-as-code patterns for AI and machine learning workloads • Create platformtoolingthatstandardizes deployment practicesof AI and ML capabilitiesacross teams.establishing reusable engineering patterns and best practices • Build observability solutions that track model health, service reliability, cost, performance, AI safety metrics, and business outcomes. • Implement scalable evaluation and monitoring frameworks for LLMs, agentic workflows, and generative AI applications. • Partner withscientists and engineers toproductionizenewMLmodels and AI capabilities. • Support governance, auditability, reproducibility, and model lifecycle management requirements. • Strongly advocate and demonstrateoperational excellence practices includingplatform automation,reliability improvements,incident response, root cause analysis • Design, revise, and document architecture patterns, operational procedures, and engineering best practices guiding technical decisions and implementation approaches providing technical guidance and mentorship to other engineers Salary Range: $ 160,000- $170,000 USD (plus bonus) Desired Skills & Experience • Strong experience building and operating ML, AI, data, or cloud platforms in production environments • Deep hands-on expertise with Databricks, including Workflows, Delta Lake, Delta Live Tables, Unity Catalog, Asset Bundles,MLflow, Python,PySpark, andSparkSQL • Experience with modernMLOpspractices including CI/CD, automated testing, model deployment, feature management, observability, and governance • Experience working with LLMs, agentic AI systems, evaluation frameworks, AI safety controls, and model monitoring solutions • Experience with model serving architectures, APIs, MCP servers, and scalable inference systems • Understanding of production support, incident management, and operational excellence practices • Strong communication skills and the ability to work effectively across multidisciplinary teams that make use of the AI and ML workflows you build. • Demonstrated ability to guide technical architecture, establish engineering best practices, and mentor engineers across teams Why work at Curinos? • Competitive benefits, including a range of Financial, Health and Lifestyle benefits to choose from • Flexible working options, including home working, flexible hours and part time options, depending on the role requirements – please ask! • Unlimited PTO policy, floating holidays, volunteering days and a day off for your birthday • Learning and development tools to assist with your career development • Work with industry leading Subject Matter Experts and specialist products • Regular social events and networking opportunities • Collaborative, supportive culture, including an active DE&I program • Employee Assistance Program which provides expert third-party advice on well-being, relationships, legal and financial matters, as well as access to counselling services Applying We know that sometimes the 'perfect candidate' doesn't exist, and that people can be put off applying for a job if they don't meet all the requirements. If you're excited about working for us and have relevant skills or experience, please go ahead and apply. You could be just what we need! If you need any adjustments to support your application, such as information in alternative formats, special requirements to access our buildings or adjusted interview formats please contact us at careers@curinos.com and we’ll do everything we can to help. Inclusivity at Curinos We believe strongly in the value of diversity and creating supportive, inclusive environments where our colleagues can succeed.  As such, Curinos is proud to be an Equal Opportunity Employer. We do not discriminate on the basis of race, color, ancestry, national origin, religion, or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other protected characteristics.

Requirements

Must-haves

Curinos operates under a hybrid modality and has office locations in New York, Chicago, Boston, Toronto, and London. This role is open to hybrid/ remote candidates based in the United States.
Design, build, and maintain platform capabilities for deploying, monitoring, and operating ML models, LLM applications, and agentic AI workflows.providing technical direction on architecture and scalability
Develop automated CI/CD pipelines and infrastructure-as-code patterns for AI and machine learning workloads
Create platformtoolingthatstandardizes deployment practicesof AI and ML capabilitiesacross teams.establishing reusable engineering patterns and best practices
Build observability solutions that track model health, service reliability, cost, performance, AI safety metrics, and business outcomes.
Implement scalable evaluation and monitoring frameworks for LLMs, agentic workflows, and generative AI applications.
Partner withscientists and engineers toproductionizenewMLmodels and AI capabilities.
Support governance, auditability, reproducibility, and model lifecycle management requirements.
Strongly advocate and demonstrateoperational excellence practices includingplatform automation,reliability improvements,incident response, root cause analysis
Desired Skills & Experience
Strong experience building and operating ML, AI, data, or cloud platforms in production environments
Deep hands-on expertise with Databricks, including Workflows, Delta Lake, Delta Live Tables, Unity Catalog, Asset Bundles,MLflow, Python,PySpark, andSparkSQL
Experience with modernMLOpspractices including CI/CD, automated testing, model deployment, feature management, observability, and governance
Experience working with LLMs, agentic AI systems, evaluation frameworks, AI safety controls, and model monitoring solutions
Experience with model serving architectures, APIs, MCP servers, and scalable inference systems
Understanding of production support, incident management, and operational excellence practices
Strong communication skills and the ability to work effectively across multidisciplinary teams that make use of the AI and ML workflows you build.
Demonstrated ability to guide technical architecture, establish engineering best practices, and mentor engineers across teams
Why work at Curinos?
Competitive benefits, including a range of Financial, Health and Lifestyle benefits to choose from
Flexible working options, including home working, flexible hours and part time options, depending on the role requirements – please ask!
Learning and development tools to assist with your career development
Work with industry leading Subject Matter Experts and specialist products
Regular social events and networking opportunities

Nice-to-haves

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Application prep

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Keywords to mirror

aimlmachine learningllmci/cdpythongo

Platform: adp-workforce-now
Effort: medium

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