The Engineer, AI Strategy & Solutions is responsible for designing and building AI-enabled and conventional software systems that integrate with enterprise data platforms, services, and event-driven architectures to deliver measurable business value. This role translates complex business and technical requirements into scalable, production-ready solutions—including APIs, data pipelines, and model serving infrastructure (batch and real-time)—using established platform patterns.
Key responsibilities include implementing AI capabilities such as inference, retrieval-augmented generation (RAG), and evaluation workflows, while ensuring compliance with Responsible AI principles, security standards, and privacy controls throughout the development lifecycle.
The engineer owns the quality of delivered solutions, including comprehensive testing (unit, integration, end-to-end), performance profiling, and observability through logs, metrics, and traces. Participation in on-call rotations and incident response is expected.
This role collaborates closely with cross-functional teams including Product, Data Science, Security, and Infrastructure. It involves contributing to design reviews, authoring clear technical documentation and runbooks, and advancing shared libraries, SDKs, and CI/CD/MLOps practices. #LI-DNI
- Required: Proficient in Python plus one of C#/Java/Go/TypeScript/C++; experienced with REST/gRPC APIs, microservices, event-driven architecture, and integration with internal/external services. Works with SQL/NoSQL and data pipelines (ETL/ELT, batch/streaming); familiar with Kafka/Kinesis/PubSub or similar. Deploys on AWS/Azure/GCP using containers/Kubernetes, IaC, and CI/CD; applies MLOps basics (model registry/versioning, feature stores, drift detection). Applies security-by-design (authN/Z, secrets, PII handling) and Responsible AI practices (model cards, eval gates); writes maintainable docs and performs effective code reviews.
- Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.
- Consistent attendance is a job requirement.
- Bachelor’s degree in a relevant technical field — e.g., Computer Science, Software Engineering, Computer Engineering, Data Science/Analytics, Electrical Engineering (software focus), or Systems Engineering — or equivalent demonstrated skill and experience (e.g., production-software/AI systems, open-source contributions, published work) required; or equivalent combination of education and experience.
- Master’s degree in Computer Science, AI/ML, Data Science, Software Engineering, or a closely related field preferred.
- Graduate coursework or certifications in machine learning, distributed systems/cloud, MLOps, security/privacy, or data engineering are a plus.
- 5+ years delivering multi-platform, networked software (web, mobile, services, edge) to production.
- Hands-on AI solutioning (e.g., computer vision, NLP/RAG, anomaly detection, personalization) with training & inference pipelines, evaluation, and monitoring; or equivalent combination of education and experience.
Your talent, skills and experience will be rewarded with a competitive compensation package.
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