Senior AI Engineer

Description

The company is a global consulting firm that uses digital technology to help businesses change for the better. Its work spans artificial intelligence, consulting, digital, cloud and DevOps, data, and software engineering, mostly for financial services and technology firms.

The FinLabs research group builds solutions in areas such as artificial intelligence, blockchain, data science models, digital underwriting, and mobile-first applications.

The company has more than 20 years in business, a workforce of 17,000+, and 58 offices in 22 countries.

The team is looking for a hands-on Senior AI Engineer to design, build, and deploy production-grade AI solutions. You will combine strong software engineering skills with practical experience running AI systems at scale, working with Java, Python, and Google Cloud Platform (GCP).

You will work closely with product managers, data scientists, software engineers, and business stakeholders to deliver reliable, scalable, and measurable AI solutions.

Responsibilities

• Design, develop, and maintain production-grade AI and machine learning applications.
• Build scalable backend services, APIs, data pipelines, and AI platforms in Java and Python.
• Develop and integrate generative AI, machine learning, natural language processing, recommendation, or other applied AI solutions.
• Deploy, monitor, optimize, and troubleshoot AI workloads on GCP.
• Work with GCP services such as Vertex AI, BigQuery, Cloud Run, GKE, Pub/Sub, Cloud Storage, Cloud Functions, and related platform technologies.
• Build reliable model-serving and inference systems that focus on performance, scalability, security, and cost efficiency.
• Put production AI practices in place, including model versioning, evaluation, observability, drift monitoring, testing, and continuous improvement.
• Work with data scientists and ML engineers to move models into production and connect them to enterprise applications.
• Write secure, maintainable, well-tested software using modern engineering practices.
• Take part in architecture reviews, technical design discussions, code reviews, and engineering standards work.
• Assess emerging AI technologies for their fit with business and product needs.
• Mentor engineers and help shape best practices for AI engineering and cloud-native software delivery.

Requirements

• 7, 10 years of professional software engineering experience, including substantial experience delivering AI or machine learning solutions.
• Strong hands-on programming skills in Java and Python.
• Proven experience building and running production AI or ML systems, not only research or proof-of-concept work.
• Strong experience with Google Cloud Platform, including cloud-native development, deployment, monitoring, and security.
• Experience designing RESTful APIs, microservices, distributed systems, and event-driven architectures.
• Solid understanding of machine learning concepts, model lifecycle management, data preparation, evaluation, and inference.
• Experience with engineering best practices: automated testing, CI/CD, version control, code quality and review, containerization, and monitoring and observability.
• Experience deploying applications with Docker and Kubernetes or GKE.
• Strong grasp of application security, scalability, reliability, and performance optimization.
• Ability to turn unclear business or product requirements into practical technical solutions.
• Excellent communication, collaboration, and problem-solving skills.
• Preferred, not required: experience with Vertex AI, generative AI, large language models, prompt engineering, retrieval-augmented generation, vector databases, or AI agents.
• Preferred, not required: experience with ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, LangChain, or equivalent.
• Preferred, not required: familiarity with MLOps platforms, model registries, feature stores, and automated model evaluation.
• Preferred, not required: experience with BigQuery, Apache Beam, Dataflow, Dataproc, or other large-scale data processing tools.
• Preferred, not required: knowledge of responsible AI, model governance, privacy, explainability, and bias mitigation.
• Preferred, not required: experience building enterprise AI applications with high availability and strict latency or security requirements.
• Preferred, not required: relevant Google Cloud or machine learning certifications.

Conditions

Base salary varies by geography and other factors. Where the role is filled in New York, NY, the base salary is $115k - $130k per year, plus benefits.

Equal opportunity employer; employment decisions are based on business needs, job requirements, and individual qualifications.

Benefits

• Highly competitive compensation and benefits package.
• Work abroad possibility across the company's 58 offices in 22 countries.
• 10 days of paid annual leave, plus sick leave and national holidays.
• Maternity and paternity leave plans.
• Comprehensive insurance covering medical, dental, vision, life, and long- and short-term disability (plans vary by region).
• Retirement savings plans.
• Higher education certification policy.
• Commuter benefits (varies by region).
• Training focused on skills, substantive knowledge, and personal development.
• On-demand access to Udemy for Business with more than 5,000 curated courses.
• Coaching from experienced colleagues in FinLabs and Centers of Excellence.
• Projects at leading tier-one banks, financial institutions, and insurance firms.
• A flat, approachable organization with a diverse, global culture.