Lead AI Platform Engineer (Python, Cloud & GenAI)

TransUnion is seeking a highly skilled Lead Engineer to join a dynamic team focused on developing next-generation AI-powered platforms and cloud-native solutions. This role involves designing, building, and operating production-grade systems that integrate software engineering, cloud infrastructure, and advanced AI applications. The ideal candidate will have deep expertise in Python, strong experience with Google Cloud Platform (GCP), and a proven track record of deploying Generative AI solutions at enterprise scale. This position offers the opportunity to work on cutting-edge technologies, influence architectural direction, and collaborate closely with cross-functional teams to deliver scalable, secure, and reliable intelligent systems. The role is hybrid, requiring a minimum of two days per week onsite at a TransUnion office.

Key Responsibilities

- Lead the design and development of high-performance Python services and applications, establishing coding standards, reusable frameworks, and best practices to ensure reliable software delivery.
- Architect scalable microservices and APIs using Python frameworks such as FastAPI and Flask, defining service boundaries and communication patterns for distributed systems.
- Design distributed, event-driven, and asynchronous systems with a focus on concurrency, fault tolerance, and horizontal scaling to meet high throughput and low-latency requirements.
- Develop comprehensive testing strategies, including unit, integration, contract, and end-to-end testing, while championing code reviews and automated quality gates.
- Create reusable Python libraries, SDKs, and templates to standardize engineering patterns and accelerate development across teams.
- Implement cloud-native architectures on GCP using services like GKE, Cloud Run, Cloud Functions, and App Engine, focusing on containerization, orchestration, autoscaling, and resilient infrastructure.
- Architect scalable data infrastructure and pipelines leveraging BigQuery, Pub/Sub, Cloud Storage, Dataflow, and Cloud Composer for real-time and batch processing.
- Establish infrastructure-as-code practices using Terraform and automate CI/CD pipelines to ensure fast, repeatable, and auditable deployments.
- Implement observability solutions with Cloud Monitoring, Logging, and Trace, define SLOs/SLIs, and lead incident response to minimize downtime.
- Enforce cloud security best practices including IAM policies, VPC design, secrets management, and cost optimization strategies.
- Design and build production applications powered by large language models (LLMs), integrating commercial and open-source models with abstraction layers for prompt engineering and token optimization.
- Develop scalable Retrieval-Augmented Generation (RAG) pipelines using embeddings, vector databases, semantic retrieval, and knowledge stores.
- Define engineering standards for AI evaluation, including golden datasets, regression testing, and task-success metrics.
- Lead model serving and inference architecture on Vertex AI and similar platforms, managing model selection, routing, versioning, latency, and cost.
- Define patterns for agentic AI systems including workflow orchestration, state management, human-in-the-loop controls, and long-running workflows.
- Provide technical leadership through architecture reviews, problem resolution, and mentoring engineers to raise overall engineering quality.
- Collaborate with data scientists, platform teams, security, product management, and business stakeholders to translate requirements into scalable solutions.
- Communicate technical strategy, architecture decisions, and risks clearly to leadership and cross-functional teams.

Required Qualifications

- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- 7+ years of experience in software, platform, cloud, data, or AI engineering with significant hands-on ownership of production systems and architecture.
- Proven expertise in Python development with frameworks such as FastAPI, Flask, asyncio, and pytest.
- Strong knowledge of distributed systems, API design, concurrency, asynchronous programming, and software architecture.
- Extensive experience with Google Cloud Platform services including GKE, Cloud Run, BigQuery, Pub/Sub, Cloud Storage, Dataflow, Vertex AI, Cloud Build, IAM, and Cloud Monitoring.
- Proficiency with infrastructure-as-code tools like Terraform and container orchestration technologies such as Kubernetes and Docker.
- Solid understanding of cloud-native architecture patterns, high availability, disaster recovery, and cost optimization.
- Experience with deep learning concepts, Transformer architectures, tokenization, embeddings, and modern ML frameworks such as PyTorch and Hugging Face.
- Hands-on experience building production applications using LLMs, Generative AI, RAG pipelines, vector databases, and agentic AI.
- Familiarity with observability tools like Prometheus, Grafana, OpenTelemetry, and cloud-native monitoring solutions.
- Demonstrated technical leadership skills, including system design, mentoring, and influencing engineering standards.

Preferred Qualifications and Benefits

- Familiarity with additional programming languages such as Java, Go, or TypeScript is advantageous.
- Opportunity to work within TransUnion’s Workforce for Good initiative, fostering professional growth, innovation, and work-life balance.
- Collaborative environment with access to cutting-edge technology and a culture that values continuous learning, ownership, and technical excellence.

Join TransUnion to contribute to pioneering AI and cloud solutions that drive meaningful business impact while advancing your career in a supportive and innovative setting.