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GE Vernova · 22 hours ago

Senior Software Architect - Generative AI

Niskayuna, NY

Full-time

Onsite

Senior Level, Lead/Staff

$161K/yr - $242K/yr

10+ years exp

GE Vernova is a leader in driving the energy transition through innovative technologies and research. They are seeking a Senior Generative AI Software Architect to define and deliver scalable AI solutions, focusing on architecting systems that leverage advanced generative AI to solve complex business problems.

EnergyEnergy EfficiencySustainability

No H1B

U.S. Citizen Only

Responsibilities

Architect and oversee the development of robust, scalable systems for deploying generative AI models

Collaborate with stakeholders to define business requirements and technical specifications for generative AI applications

Guide the selection, customization, and optimization of state-of-the-art generative AI models

Develop end-to-end pipelines for model training, inference, and monitoring in production environments

Ensure systems meet high standards for performance, scalability, and security while adhering to data privacy regulations

Lead the implementation of APIs, microservices, and frameworks to integrate AI models into enterprise solutions

Design scalable and efficient architectures for generative AI models, applications, and workflows

Ensure seamless integration of generative AI capabilities into existing systems

Provide mentorship to engineering teams, fostering expertise in AI and software architecture

Design and maintain platforms to handle large-scale solution applications in collaboration with legal/compliance teams

Define architectural best practices to mitigate risks associated with Generative Ai (e.g., model hallucinations)

Align AI architecture with organizational goals and contribute to strategic technology roadmaps

Document architectural designs, workflows, and decisions for transparency and scalability

Qualification

Generative AI architectureCloud computing AWSCloud computing AzureCloud computing GCPNeural network architecturesMLOps/LLMOpsAPI developmentPerformance optimizationSecurityComplianceLeadershipStrategic thinkingProblem-solvingCommunication skills

Required

Master's degree or higher in Computer Science/Engineering, AI, or related fields

10+ years of experience in software architecture with a focus on AI/ML systems

Proven track record of designing scalable Generative AI use case solutions

Exceptional leadership, strategic thinking, and problem-solving abilities

Excellent communication skills for engaging with stakeholders across technical and business domains

Must be willing to work out of an office located in Niskayuna, NY

Legal authorization to work in the U.S. is required. We will not sponsor applicants at the Master's level, now or in the future, for this job opening

Must be 18 years or older

Strong knowledge of neural network architectures (e.g., CNNs, RNNs, Transformers)

Expertise in designing scalable, distributed architectures for AI systems

Strong experience with cloud computing platforms (AWS, Azure, GCP) and containerization (Kubernetes, Docker)

Familiarity with large-scale distributed systems and database technologies

Experience in creating technical design documents and implementation playbooks for target-state AI solutions within cloud environments based on

Experience translating business requirements into technical solution designs

Thorough understanding of integration platforms and protocols (e.g., REST, SOAP, HTTP, UDP, ETC.)

Proficiency in designing RESTful APIs and GraphQL endpoints for AI services

Knowledge of API development, microservices architecture, and DevOps practices

Proficiency in MLOps/LLMOps and model lifecycle management, including CI/CD pipelines for training, testing, and deploying AI models at scale

Expertise in prompt engineering and fine-tuning large language models (LLMs), including techniques like Reinforcement Learning from Human Feedback (RLHF) and parameter-efficient tuning (e.g., LoRA)

Performance optimization for AI/ML workloads, including GPU/TPU acceleration, model quantization, pruning, and distillation

Observability & Monitoring of AI pipelines, encompassing logging, tracing, and metrics to detect drift, anomalies, or performance bottlenecks

Security, Privacy, and Compliance knowledge, with an understanding of data governance (GDPR, HIPAA, SOC 2) and secure model serving