The AI Solution Lead will work closely with engineering teams and client stakeholders to translate cutting-edge AI capabilities into reliable production systems, while ensuring governance, transparency, and responsible AI practices.

The ideal candidate combines technical depth, research awareness, and strong communication skills, enabling them to represent our company confidently in front of senior client stakeholders.

Key Responsibilities

AI Solution & Design

• Design and deliver enterprise-grade AI solutions leveraging Generative AI and Large Language Models.
• Define designs for LLM-based systems, agentic workflows, retrieval-augmented generation (RAG), and AI copilots.
• Evaluate and select appropriate models, frameworks, and infrastructure for production AI systems.
• Ensure scalability, reliability, and performance of deployed AI solutions.

Machine Learning & Model Expertise

• Provide deep technical expertise in:
• Large Language Models (LLMs)
• Transformer architectures
• Generative AI techniques
• Model evaluation and benchmarking
• Design approaches for fine-tuning, prompt engineering, and model adaptation.
• Guide teams on best practices in ML pipelines, experimentation, and model lifecycle management.

Production Deployment & MLOps

• Lead deployment of machine learning and GenAI systems into production environments.
• Architect and implement MLOps pipelines, model monitoring, and continuous improvement processes.
• Ensure AI systems are secure, scalable, and operationally maintainable.

AI Governance & Responsible AI

• Implement frameworks for:
• AI governance
• Model explainability
• Transparency
• Risk management
• Ensure compliance with enterprise AI governance standards and regulatory expectations.
• Define policies for model validation, bias mitigation, and responsible deployment.

Client Engagement & Technical Leadership

• Act as a trusted technical advisor to client stakeholders.
• Clearly communicate complex AI concepts to executives, architects, and engineering teams.
• Represent the company with credibility in technical and strategic discussions around AI adoption.
• Work closely with client teams to translate business problems into AI-driven solutions.

Research & Innovation

• Stay current with emerging developments in:
• Generative AI
• Large language models
• AI agents and agentic architectures
• AI infrastructure and tooling
• Evaluate new research and technologies to determine their practical applicability in enterprise environments.
• Help shape the organization’s AI strategy and technical direction.

Required Qualifications

• Master’s degree in Data Science, Machine Learning, Computer Science, or related field.
• Strong expertise in machine learning fundamentals and modern generative AI technologies.
• Proven experience designing and deploying AI/ML systems in production environments.
• Deep knowledge of:
• Large Language Models
• Generative AI architectures
• ML pipelines and model lifecycle management
• Experience working with AI frameworks and ecosystems used for building GenAI applications.
• Experience implementing AI governance, explainability, and responsible AI practices.
• Strong understanding of enterprise software architecture and distributed systems.

Preferred Qualifications

• Experience with agentic AI systems and orchestration frameworks.
• Experience building RAG-based AI systems.
• Familiarity with AI platform engineering and scalable AI infrastructure.
• Contributions to AI research, open-source projects, or technical publications.
• Experience working with enterprise clients in regulated industries.

Key Skills

Technical Skills

• Machine Learning & Data Science
• Large Language Models (LLMs)
• Generative AI systems
• AI agents and agentic framework
• MLOps and model lifecycle management
• AI governance and explainability

Professional Skills

• Strong analytical and problem-solving capabilities
• Excellent communication and presentation skills
• Ability to simplify complex AI concepts for diverse audiences
• Collaborative mindset and ability to work effectively within teams
• Client-facing professionalism and credibility

Work Environment

• Full-time in-office role with collaboration across engineering and client teams.
• Weekly client visits for workshops and solution design sessions.
• High collaboration with data scientists, engineers, architects, and business stakeholders.

What Success Looks Like in This Role

• Successfully designed and deliver production-grade AI systems.
• Become a trusted AI advisor to both internal teams and client stakeholders.
• Ensure responsible and governed adoption of AI technologies.
• Help organizations translate GenAI innovation into real operational value.

Robots & Pencils is seeking a seasoned AWS AI Solutions Architect to lead the design and delivery of complex, enterprise-grade generative and agentic AI systems built on Amazon Web Services. You will architect scalable, secure, and production-ready AI platforms leveraging Amazon Bedrock, Amazon Bedrock AgentCore, AWS Strands Agents, AWS AgentCore Gateway, Nova Forge, Nova 2 Sonic, and related AWS AI/ML services. 
 
As an AWS AI Solutions Architect, you will serve as a strategic technical advisor—translating ambiguity into structured AWS-native architectures, validating designs through hands-on prototyping, and ensuring every solution aligns with the AWS Well-Architected Framework (including ML Lens) while delivering measurable business value. 

Key Responsibilities 

Client Engagement & AWS Solutions Architecture 

• Serve as the primary AWS AI architecture partner for strategic clients, driving generative and agentic AI system design from discovery through production. 

• Lead architecture design using Amazon Bedrock (including foundation models and custom models), Bedrock AgentCore, AWS Strands Agents, and AWS AgentCore Gateway. 

• Design advanced RAG, Agentic RAG, and multi-agent orchestration architectures leveraging AWS-native services such as Lambda, Step Functions, API Gateway, DynamoDB, Aurora (pgvector), and OpenSearch. 

• Produce AWS reference architectures, architecture decision records (ADRs), and implementation roadmaps aligned to business objectives. 

• Validate feasibility through hands-on prototyping in Python using Bedrock SDKs, SageMaker, and serverless services. 

• Ensure architectures follow AWS security best practices (IAM, KMS, VPC, PrivateLink) and cost optimization principles. 

Outcome Ownership & Business Impact 

• Own architectural integrity from concept through production deployment on AWS. 

• Align solutions with AWS Well-Architected Framework pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability. 

• Guide clients through tradeoff decisions across model selection (Bedrock FMs vs custom SageMaker models), latency, cost, governance, and compliance. 
  Accelerate time-to-value through reusable AWS accelerators, Infrastructure as Code (CloudFormation/Terraform/CDK), and CI/CD automation. 

• Continuously evaluate emerging AWS AI capabilities (Nova Forge, Nova 2 Sonic, Bedrock updates, and new AgentCore capabilities). 

Engineering Leadership & Delivery Excellence 

• • Provide architectural oversight to Forward Deployed Engineers and AWS delivery teams. 

• Establish best practices for MLOps on AWS including model lifecycle management, monitoring, and observability using SageMaker, CloudWatch, CloudTrail, and AWS Config. 

• Define governance, responsible AI guardrails, Bedrock Guardrails configuration, and security controls for enterprise environments. 

• Mentor engineers on AWS AI service integration, distributed systems design, and secure multi-account strategies. 

• Make principled tradeoffs under constraints related to privacy, compliance (SOC2, HIPAA, GDPR), cost, and operational complexity. 

Cross-Functional Collaboration 

• Partner with internal product, engineering, research, and customer success teams to evolve AWS-based AI offerings. 

• Contribute AWS reference architectures and reusable infrastructure modules to internal accelerators. 

• Support pre-sales engagements including architecture workshops, AWS migration strategy, and solution scoping. 

• Collaborate across distributed teams and client stakeholders across North America. 

Required Skills & Qualifications 

• Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
  • 7–10+ years of experience in software engineering or cloud architecture with deep AWS ownership. 
  • Deep expertise in Amazon Bedrock, Bedrock AgentCore, AWS Strands Agents, AgentCore Gateway, and related AWS AI services. 
  • Strong familiarity with SageMaker (training, deployment, pipelines), deep learning fundamentals, and model fine-tuning strategies. 
  • Experience architecting RAG, multi-agent, and orchestration systems using AWS-native services. 
  • Strong knowledge of distributed systems, event-driven architectures, and serverless patterns. 
  • Proficiency with Infrastructure as Code (AWS CDK, CloudFormation, Terraform). 
  • Hands-on development capability in Python and AWS SDKs. 
  • Experience implementing observability and monitoring strategies in AWS environments. 
  • Proven success leading enterprise-scale AWS transformations. 
  • Exceptional communication skills for both technical and executive audiences. 
  • AWS Professional Certifications highly preferred (AWS Solutions Architect – Professional, AWS DevOps Engineer – Professional). 

Nice to Have 

• AWS Specialty certifications (Machine Learning – Specialty, Security – Specialty).
  • Experience with advanced agentic reasoning patterns (ReAct,CoT, Tree-of-Thoughts) implemented on Bedrock. 
  • Experience building secure multi-account AWS organizations using Control Tower. 
  • Exposure to data engineering services such as Glue, Redshift, Lake Formation. 
  • Consulting or professional services background. 

Personal Competencies 

• Accountability – Owns AWS architectural direction and client outcomes with rigor.
  • Adaptability – Rapidly adopts new AWS AI releases and evolving generative AI capabilities.
  • Collaboration – Builds trust across engineering and executive stakeholders. 
  • Execution-Focused – Balances innovation with production-ready AWS delivery. 
  • Innovation-Minded – Experiments responsibly with emerging AWS AI services. 
  • Craftsmanship – Designs secure, scalable, and well-documented AWS systems. 
  • Leadership with Courage – Drives architectural alignment in complex environments. 
  • Comfort in Ambiguity – Translates unclear AI requirements into AWS-native solution architectures. 

Why Join Robots & Pencils? 

We build smart systems for a human world — blending creativity, engineering, and AWS-powered AI to help organizations reimagine how they work. As an AWS AI Solutions Architect, you will shape enterprise-scale generative and agentic AI platforms using the most advanced AWS services available. You will define architectures that deliver measurable business value, mentor teams, and directly influence the evolution of our AWS AI practice. 

Role: Principal Data Scientist - Commercial Analytics

Title: Senior Lead, Principal Data Scientist / Associate Director - Data Science

Location: NY / NJ (USA)

Summary:  The role is expected to serve as the primary client-facing data science lead for commercial analytics and RGM engagements. In this role, you will partner with senior client stakeholders, translate business challenges into data science solutions, review and guide offshore deliverables, and ensure delivery of high-quality outcomes. You will combine hands-on modeling expertise with client leadership, solution ownership, and team guidance to drive measurable business impact Provide clear guidelines for offshore development teams & own outcomes. You will nurture key client relationships to ensure client account success

Desired Experience : 

• 8–12 years of overall experience.
• 3+ years in consulting or client-facing analytics roles.
• 3+ years of experience in CPG or adjacent commercial analytics environments.
• Proven experience engaging with senior stakeholders and leading client conversations.
• Strong track record in data science, statistics, and machine learning

Role & Responsibilities :

• Develop and refine analytics & ML models and tools (e.g., Price Elasticity, iPPA diagnostics, Portfolio Simulators, TPO, TPM etc.) to support strategic RGM decisions
• Employ your analytical skills to decipher large datasets, and identify opportunities to enhance existing solutions, as well as develop new ones as scalable proof-of-concepts (PoC).
• Work closely with cross-functional teams, including data scientists, data engineers and product managers and business experts to ensure the smooth development of RGM models and translate outcomes to business stakeholders
• Collaborate extensively with business stakeholders to gather requirements, deeply understand challenges and identify opportunities.
• Leading client workshops where broad vision and ambiguous business problems are articulated to be solved through data analytics and AI
• Independently liaise with customers and convincingly present solutions in an unstructured and ever-changing client environment. Be able to independently question the customer, when required.
• Perform a role that involves a combination of hands-on contribution and customer engagement
• Contribute to organization building through training, mentoring, and developing repeatable analytic approaches

Primary Skills (Mandatory)

• Strong foundation in ML and statistical concepts.
• Proficiency in SQL, Python, and PySpark.
• Experience with Snowflake, BigQuery, Azure, AWS, or Databricks.
• Experience with CPG data and commercial analytics, including pricing, promotion, mix, e-commerce, or customer analytics.
• Ability to convert rigorous analysis into strategic recommendations.
• Strong project management, communication, and team leadership skills
• Strong problem-solving skills and a creative mindset for disrupting how RGM analytics is conducted today. Be at the forefront of innovations in commercial analytics space

 Secondary Skills (Good to have):

• Exposure to supply chain analytics, manufacturing analytics, or e-commerce analytics.
• Data engineering / MLOps experience.
• Dashboarding experience with Power BI or Tableau
• Exposure to Agentic AI / LLMs or any other Gen AI capabilities

Who We Are

Cross River builds the infrastructure behind the world’s most innovative financial products. Our technology and capital solutions power payments, cards, lending, and digital asset capabilities that move money safely, instantly, and inclusively — trusted by leading fintechs, enterprises, and disruptors across the globe.

Our mission is simple: to build the financial infrastructure that expands access and opportunity for all. Guided by a culture of collaboration, curiosity, and purpose, Cross River has been named one of American Banker’s Best Places to Work in Fintech year after year. Whether you’re designing code, solving regulatory puzzles, or developing strategy, you’ll join a team where innovation and integrity drive everything we do — and where your work helps shape the future of finance.

What We're Looking For

The AI Transformation Manager reports to the Chief Data and AI Officer and plays a critical role in driving Cross River’s AI-led transformation and commercialization strategy. This position is responsible for orchestrating the end-to-end implementation of AI initiatives across the enterprise—bridging strategy, productization, compliance, and delivery to ensure measurable business impact. The ideal candidate combines deep expertise in AI/ML program management with a pragmatic understanding of financial services and regulatory environments.

Responsibilities:

Strategy & Governance

• Define and manage the AI Transformation roadmap, ensuring alignment with Cross River’s strategic objectives, regulatory standards, and innovation priorities.
• Partner with business, data, and technology leaders to identify AI-driven opportunities for efficiency, risk management, and new revenue models.
• Establish a governance framework for AI projects, including evaluation metrics, responsible AI principles, and lifecycle management.
• Oversee commercialization of AI capabilities, enabling scalable deployment of internal tools and potential external monetization opportunities.

Program Execution & Delivery

• Lead the planning, coordination, and execution of AI initiatives across multiple business domains—banking, lending, risk, compliance, and customer experience.
• Develop and maintain a portfolio management system for all AI programs, ensuring transparency on timelines, costs, dependencies, and outcomes.
• Ensure data readiness and model governance across all AI deployments in close partnership with data engineering and compliance teams.
• Track and report on transformation metrics, including adoption, ROI, and productivity gains.

Collaboration & Change Management

• Partner with product, engineering, operations, and risk teams to embed AI solutions into enterprise workflows.
• Drive organizational change management to enable smooth adoption of AI technologies, ensuring training and alignment across teams.
• Serve as a liaison between business and technical teams, translating complex AI capabilities into actionable business insights.
• Promote a culture of responsible AI innovation that balances experimentation with ethical standards and risk management.

Commercialization & Market Enablement

• Identify opportunities to externalize AI capabilities through partnerships, APIs, and new product lines.
• Collaborate with external vendors, startups, and research organizations to expand the bank’s AI ecosystem.
• Support the Chief Data and AI Officer in defining AI monetization strategies and evaluating go-to-market models.

Basic Qualifications:

• 10+ years of experience in technology, analytics, or transformation roles, with at least 5 years in AI/ML program or product management.
• Proven experience leading cross-functional AI initiatives from conception through implementation in a regulated industry (preferably financial services, fintech, or banking).
• Strong understanding of AI platforms, MLOps, model governance, and data management frameworks.
• Experience managing stakeholder engagement, budgets, and vendor relationships for large-scale transformation programs.
• Exceptional ability to translate technical AI concepts into business outcomes and communicate effectively at all organizational levels.

Preferred Qualifications:

• Master’s degree in Business, Data Science, Engineering, or a related field.
• Prior experience applying AI solutions in regulated environments, such as banking, healthcare, or insurance.
• Familiarity with AI governance frameworks, including bias mitigation, interpretability, and model monitoring.
• Experience in commercialization or business development related to AI-driven products or services.
• PMP, Agile, or equivalent program management certification preferred.

Leadership & Impact:

The ideal candidate will demonstrate a track record of driving complex, multi-stakeholder AI initiatives, combining visionary thinking with disciplined execution. They will be a trusted advisor to the Chief Data and AI Officer and a change leader influencing how AI transforms Cross River’s core business and innovation strategy.

#LI-JJ1 #LI-Hybrid #LI-Onsite

Salary Range: $170,000.00 - $200,000.00