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TypeAgent infrastructure126 Agent engineering153 Developer tooling2 Applied research11 Forward deployed179 Other1

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26 of 472 matching

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New York City, NY, United States; San Francisco, CA, United States (Hybrid)
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Foster City, CA, United States (Remote)
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Staff Software Engineer-AI
Moody's Corporation
London, England, United Kingdom
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Staff/Sr. Staff Software Engineer, Product Engineering
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San Francisco, California, United States (Hybrid)
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Ingénieur IA (Niveau Staff) / Staff AI Engineer
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New York City, New York, United States
$200k–$265k/yr
1d agoTop pickNew

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Agent infrastructureStaffNew

Staff Software Engineer-AI

Moody's CorporationLondon, England, United Kingdom

Posted 1d ago/Full-time/Expires Nov 10, 2026

Apply on company site

Why it matters

The role owns production agentic workflows, tool integration, prompt orchestration, evaluations, inference pipelines, and reusable AI platform components. It combines hands-on coding with technical direction for enterprise-scale real-time and batch AI workloads.

About the job

Skills And Competencies

8+ years of experience in software engineering, with deep hands-on experience designing, coding, testing, and operating scalable, resilient, production-grade backend systems and cloud-native services
Expert-level coding capability in modern programming languages such as Python, TypeScript, Go, or similar, with the ability to personally contribute high-quality production code while guiding technical direction
Deep hands-on expertise building enterprise AI applications using large language models, AI agents, retrieval-augmented generation, prompt engineering, orchestration frameworks, evaluation methods, and model optimisation techniques
Proven ability to take complex AI solutions from prototype to production, making practical engineering trade-offs across performance, scalability, reliability, security, maintainability, and cost
Expert knowledge of cloud platforms such as Amazon Web Services, Google Cloud Platform, or Microsoft Azure, with strong experience using Docker, Kubernetes, Elastic Container Service, or equivalent technologies in production environments
Strong experience designing and implementing application programming interfaces, distributed systems, event-driven architectures, data pipelines, PostgreSQL, MongoDB, Redis, vector databases, observability, and automated deployment pipelines
Demonstrated ability to influence technical direction while remaining close to the codebase, mentoring engineers through design reviews, code reviews, pairing, debugging, and hands-on problem solving
Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using AI tools to lead innovation initiatives. Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization

Education

Bachelor's degree or higher in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field, or equivalent practical experience

Responsibilities

Design, code, and lead delivery of scalable AI platforms and intelligent applications that bring emerging AI capabilities into production

Act as a hands-on technical leader, spending significant time designing, coding, reviewing, debugging, and improving production systems that support AI-powered products and services
Design and build scalable backend services, application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scale
Implement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration
Make key technical decisions while remaining accountable for practical implementation quality, including code maintainability, system performance, reliability, security, scalability, and cost efficiency
Establish engineering best practices through hands-on contribution, code reviews, technical design reviews, automated testing, observability, monitoring, and operational excellence
Champion machine learning operations practices including model lifecycle management, prompt versioning, automated evaluation, deployment pipelines, monitoring, and continuous improvement
Partner with product managers, data scientists, machine learning engineers, engineering leaders, and business stakeholders to translate strategic priorities into robust, buildable technical solutions
Build reusable frameworks, libraries, developer tooling, and platform components that accelerate AI development across multiple teams without creating unnecessary abstraction or complexity
Evaluate emerging AI technologies through practical prototypes, proof-of-concept builds, and production-readiness assessments, then guide teams on implementation patterns and trade-offs
Mentor engineers through practical technical coaching, pairing, code reviews, design feedback, documentation, and example-setting as a senior individual contributor

About The Team

Our Digital Content and Innovation (DC&I) team is responsible for building next-generation internal and external products powered by cutting-edge artificial intelligence technologies, including large language models, AI agents, machine learning, and natural language processing. The group brings together engineers, data scientists, and AI specialists to solve complex challenges and turn breakthrough ideas into practical products that enhance productivity, unlock insights, and create measurable business impact. Collaboration is central to how the team works. Engineers contribute across the full AI lifecycle, from experimentation and prototyping through to large-scale production deployment, while helping shape reusable platforms, frameworks, and responsible AI practices. By joining the team, you will work on some of the most exciting challenges in applied AI, contribute directly to production code and architecture, and be part of a culture that values curiosity, innovation, knowledge sharing, and continuous growth.

Stack

python
typescript
go
aws
gcp
azure
docker
kubernetes

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