ABOUT OUR CLIENT
Our Client is advancing the use of Machine Learning and Generative AI across its Workplace Solutions division and is seeking a senior technical leader to help shape that transformation. This is an opportunity to influence AI strategy, architecture, governance, and adoption while delivering scalable, responsible technology solutions that enhance customer experiences, optimize operations, and create measurable business value.
ABOUT THE ROLE
As a Senior Machine Learning & Generative AI Engineer, you will provide technical leadership for the design, architecture, and implementation of enterprise AI and Generative AI solutions. You will operate at the intersection of AI/ML, software engineering, cloud architecture, and business strategy, translating emerging capabilities into secure, scalable, production-ready solutions.
This role requires more than hands-on development. You will help define technical direction, establish architectural and engineering standards, influence the AI roadmap, mentor engineers, and partner closely with business leaders and enterprise architects. You will take complex and sometimes undefined business challenges and turn them into actionable technical strategies and solutions.
You will also play a critical role in rapidly advancing Our Client’s Generative AI capabilities, helping move innovative ideas from experimentation and proof of concept through enterprise-scale production adoption.
RESPONSIBILITIES
Lead the architecture, design, development, and deployment of sophisticated AI, Machine Learning, and Generative AI solutions across the division
Leverage large language models and other AI technologies to enable intelligent automation, advanced analytics, integrated insights, and new business capabilities
Provide senior technical leadership across the AI solution lifecycle, taking initiatives from early exploration and architecture through development, production rollout, optimization, and ongoing operations
Partner with business leadership and enterprise architects to shape the strategic roadmap for Machine Learning and Generative AI capabilities, including LLM application patterns, platform modernization, and enterprise governance
Translate complex business challenges into scalable AI strategies, architectures, and technical solutions tied to measurable outcomes
Lead the development and iteration of AI/ML and Generative AI proofs of concept, data and feature pipelines, model workflows, and production applications
Facilitate technical discovery, what-if exploration, whiteboarding, architecture discussions, and design sprints to assess feasibility, identify opportunities, and validate business impact
Establish and champion engineering standards for AI quality, governance, responsible and ethical AI, regulatory compliance, security, observability, and production readiness
Drive continuous improvements in model quality and application performance through systematic experimentation, prompt engineering, evaluation frameworks, data and training versioning, and A/B testing
Implement and advance AIOps and MLOps practices that improve the reliability, scalability, deployment, monitoring, and lifecycle management of AI models and applications
Provide technical guidance and mentorship to engineers and teams developing LLM-powered applications, including context engineering, orchestration patterns, evaluation methodologies, and production integration
Create reusable architectural patterns, templates, reference implementations, and engineering practices that accelerate consistent and scalable AI adoption
Evaluate emerging Generative AI, Machine Learning, cloud, and agentic AI capabilities and determine their applicability to enterprise use cases
Integrate AI and data solutions with microservices, event-driven architectures, enterprise systems, and external business partners while ensuring scalability, security, observability, and operational readiness
Serve as a trusted technical partner to business and technology stakeholders, clearly communicating complex AI concepts, architectural decisions, opportunities, risks, and tradeoffs
Champion the responsible adoption of AI while helping teams navigate ambiguity, emerging technologies, and rapidly evolving technical requirements
QUALIFICATIONS
Bachelor’s degree in Science, Engineering, Mathematics, Statistics, Data Science, another quantitative field, or equivalent experience
At least 5 years of experience deploying and supporting full-stack applications in enterprise environments, including several years integrating AI and Machine Learning capabilities into production applications
Significant hands-on experience designing, developing, and deploying enterprise AI/ML systems and Generative AI applications
Advanced experience with Generative AI application development, large language model integration, prompt and context engineering, AI evaluation, and production optimization
Strong full-stack engineering experience spanning backend, frontend, and database technologies
Experience with modern frontend frameworks such as React or Vue
Strong proficiency with Python, TypeScript, Git, and SQL
Deep understanding of software engineering design patterns and enterprise application architecture principles
Experience designing secure, scalable, maintainable, resilient, and cost-optimized cloud-native applications
Strong experience with AWS services, particularly Amazon Bedrock, SageMaker, S3, and Lambda
Experience with infrastructure as code, including AWS CDK
Strong knowledge of CI/CD pipelines, automated testing, DevOps practices, and production software engineering
Experience implementing AIOps and MLOps practices across the AI development and deployment lifecycle
Demonstrated understanding of responsible AI principles, governance, secure model deployment, and production AI risk considerations
Ability to balance probabilistic AI approaches with deterministic software engineering patterns to create reliable, maintainable enterprise solutions
Demonstrated ability to provide technical leadership and mentorship while influencing engineering practices across teams
Strong communication skills with the ability to translate highly technical AI concepts into clear recommendations for technical and non-technical stakeholders
Proven ability to collaborate with business leaders, architects, engineers, and cross-functional partners in remote and rapidly changing environments
Strong critical thinking and problem-solving skills with the ability to bring structure and clarity to complex or undefined challenges
High learning agility with the ability to evaluate emerging technologies, adapt to changing priorities, and rapidly develop expertise in new areas
Commitment to fostering an inclusive environment that values diverse experiences, perspectives, ideas, and opinions
Ability to work remotely with access to a high-speed internet connection
Must be located in the United States or Puerto Rico
Applicants must not currently or at any point in the future require sponsorship for employment
PREFERRED QUALIFICATIONS
Group Benefits or insurance industry experience
Advanced degree in an analytical or quantitative field with demonstrated in-depth AI expertise
Advanced experience with AI/ML Ops practices, distributed data processing, and real-time data pipelines
Familiarity with data mesh principles and real-time analytics
Experience or familiarity with single-cloud or multi-cloud agentic architectures for building LLM-based applications
Experience designing production-grade AI solutions that combine probabilistic and deterministic approaches, including large language models, classical Machine Learning, and rules-based systems
Advanced experience with AI evaluation, orchestration, model and application integration, and the development of maintainable production services
BENEFITS
Strong base and bonus structure
401(k) plan with a 2% company contribution and 6% company match
Work-life balance supported through vacation, personal time, and paid holidays
[MISSING: Additional health, dental, vision, and other benefits details not provided]
WORK LOCATION
Remote
Candidates must have access to a high-speed internet connection and be located in the United States or Puerto Rico
WHY JOIN OUR CLIENT
This is an opportunity to play a senior technical role in shaping how Generative AI and Machine Learning are designed, governed, and operationalized within a complex enterprise environment. You will have the ability to influence architecture and strategy while remaining close to the technology and building solutions that move from experimentation into real-world production.
You will work across AI strategy, architecture, engineering, experimentation, governance, and production delivery while mentoring others and helping teams successfully adopt rapidly evolving AI capabilities.
Our Client values diverse experiences, perspectives, skills, and a passion for innovation. If you are an experienced AI engineer who enjoys solving complex problems, influencing technical direction, and turning emerging AI capabilities into scalable enterprise solutions, we encourage you to apply.
