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Gen Ai Platform Engineer Jobs

2 jobs found

Today

Staff AI Engineer - Global Infrastructure

American Express New York, NY

New York, NY

Today

$144k - $256k/yr Full time Backend Developer Manager Agentic Ai

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Job Description

American Express seeks a Staff AI Engineer to lead enterprise-scale AI architecture and implementation across infrastructure and agentic AI systems. This hybrid role in New York focuses on scalable, reliable, secure, and responsible AI platforms while guiding technical direction, platform risk, and continuous improvements in AI engineering practices.

Role Responsibilities

Lead enterprise-scale AI architecture and implementation spanning infrastructure and agentic AI systems.
Set technical direction for core enterprise AI platform initiatives.
Ensure AI platforms are scalable, reliable, secure, and responsible.
Mentor senior technical talent and support engineering excellence across teams.
Drive continuous improvement in AI engineering practices and platform capabilities.
Provide 24x7 support to help maintain an uninterrupted, high-quality customer and colleague experience.
Lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company.
Provide product management for core enterprise platforms.

Required Qualifications

Deep knowledge of machine learning and deep learning systems, including model architectures, training, evaluation, and optimization.
Advanced understanding of Generative AI and LLM ecosystems, including embeddings, fine-tuning, prompt design, retrieval-augmented generation, and inference at scale.
Strong understanding of AI infrastructure, including GPU platforms, accelerated compute, workload scheduling, capacity optimization, model serving, and inference performance.
Advanced understanding of agentic AI design, including planning, reasoning, tool use, memory, multi-agent coordination, and autonomy controls.
Strong foundation in distributed systems and cloud-native architecture, including Kubernetes, APIs, microservices, event-driven design, observability, and platform reliability.
Knowledge of DevOps and CI/CD platforms such as Harness, including automated deployment, environment promotion, governance, and operational controls.
Knowledge of enterprise AI governance, including model risk management, explainability, bias detection, safety, and regulatory compliance.
MS/PhD in Artificial Intelligence, Machine Learning, Computer Science, or related discipline (preferred).
12+ years of experience in AI/ML engineering, AI infrastructure, platform engineering, data engineering, or related fields, with a track record of delivering complex production systems at scale.
Proven experience architecting end-to-end AI/ML platforms across data pipelines, training, deployment, serving, monitoring, and inference optimization.
Experience designing and operating GPU-based AI infrastructure, including accelerated compute platforms, workload scheduling, utilization optimization, capacity management, and performance tuning.
Experience with cloud-native and Kubernetes-based platforms supporting training, batch workloads, inference, orchestration, observability, reliability, and cost efficiency.
Hands-on experience with Python and modern AI/ML frameworks including PyTorch, TensorFlow, Scikit-learn, Hugging Face, and related tooling.
Deep experience with agentic AI systems, including planning, tool use, memory, evaluation, retrieval, embeddings, vector databases, and agent frameworks.
Experience leading complex cross-functional technical initiatives and influencing architecture and engineering direction without direct authority.
Demonstrated ability to mentor and develop engineers at all levels, including Staff-level engineers.
Experience working in regulated environments such as financial services, including AI governance, risk management, and compliance considerations.

Technologies

Python; PyTorch; TensorFlow; Scikit-learn; Hugging Face
Kubernetes; Harness; CI/CD
LLM ecosystems; embeddings; fine-tuning; prompt design; retrieval-augmented generation
GPU platforms; accelerated compute; model serving
Vector databases; agent frameworks
Distributed systems; cloud-native architecture; APIs; microservices; event-driven design; observability

Compensation and Location

Location: New York, NY (hybrid). Salary: USD 144,250 - 256,250 per year.

Benefits

Competitive base salaries
Bonus incentives
6% Company Match on retirement savings plan
Free financial coaching and financial well-being support
Comprehensive medical, dental, vision, life insurance, and disability benefits
Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
20+ weeks paid parental leave for all parents, regardless of gender, for pregnancy, adoption or surrogacy
Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
Free and confidential counseling support through Healthy Minds program
Career development and training opportunities

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Today

Gen AI Engineer with Java & Microservices

American IT Systems Atlanta, GA

Atlanta, GA

Today

Full time Backend Developer Artificial Intelligence AWS

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Job Description

The Gen AI Engineer will design and implement production-ready AI services that use Java and a microservices architecture. The role focuses on building and deploying API layers for large language models, including RAG, monitoring, testing, and evaluation within an agile delivery environment.

Responsibilities

Design, develop, and deploy production-grade Java microservices (such as with Spring Boot) that integrate with large language models and AI/ML platforms.
Architect and implement RESTful APIs and event-driven communication patterns to deliver generative AI capabilities to internal and external clients.
Develop prompt engineering strategies, including prompt templating, chaining, and dynamic context management to improve output quality for business use cases.
Implement Retrieval-Augmented Generation (RAG), including integration with vector databases to generate grounded, context-aware responses from proprietary knowledge bases.
Build resilient model integration layers with retry logic, timeouts, rate limiting, and fallback mechanisms to support high availability.
Create services for asynchronous processing and streaming responses to support long-running inference tasks efficiently.
Implement monitoring, logging, and observability capabilities to track AI service health, including token usage, latency, and model performance.
Collaborate with data scientists and ML engineers to move experimental models into production, emphasizing architecture and performance optimization.
Develop and execute unit, integration, and load tests to ensure reliability and quality under production conditions.
Evaluate new generative AI models, libraries, and tools by providing technical assessments and recommendations.
Write technical documentation and support maintenance of internal AI service frameworks and shared libraries.
Stay current with developments in the Gen AI landscape and propose improvements to system architecture and development practices.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or a related technical field (or equivalent practical experience).
5+ years of professional software development experience, with strong object-oriented programming and enterprise application development.
Expert proficiency in Java, including concurrency, functional programming patterns, and robust error handling.
Hands-on experience building and deploying microservices, including service discovery, API gateways, and distributed tracing.
Strong working knowledge of Spring Boot or a similar Java microservice framework, including testing and configuration.
Proven experience integrating with third-party AI/LLM APIs such as OpenAI, Anthropic, or open-source models in a server-side environment.
Solid understanding of cloud platforms (AWS, GCP, or Azure) and experience with Docker and Kubernetes (highly desirable).
Proficiency with SQL and NoSQL databases and practical vector database experience (Pinecone, Weaviate, pgvector) for semantic search.
Working knowledge of observability tools and practices, including logging, metrics, and monitoring dashboards.
Excellent problem-solving, debugging, and analytical skills, with a proactive and self-directed work ethic.
Strong communication skills and the ability to collaborate effectively while translating complex technical concepts for non-technical stakeholders.
Passion for learning new technologies, particularly in generative AI and machine learning engineering.

Technologies

Java
Spring Boot
RESTful APIs
OpenAI
Anthropic
Microservices architecture
Service discovery
API gateways
Distributed tracing
AWS, GCP, Azure
Docker
Kubernetes
SQL, NoSQL
Vector databases
Pinecone, Weaviate, pgvector
Retrieval-Augmented Generation (RAG)

Location and Work Mode

Atlanta, GA (onsite).

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Gen Ai Platform Engineer Jobs

Staff AI Engineer - Global Infrastructure

Gen AI Engineer with Java & Microservices

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