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Senior AI Engineer
American Express. Serve as a technical leader on an agile team, turning complex, ambiguous problems into production-grade AI and agentic systems meeting security, compliance, and regulatory requirements .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and building LLM-powered AI systems with a strong focus on scalability, low latency, and compliance. Proven ability to lead technical teams, mentor engineers, and drive best practices in software development and deployment.
Highest-signal resume keywords
LLM DevelopmentPython ProgrammingCloud-Native ApplicationsAI System DesignTechnical Leadership
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningData StructuresAlgorithmsModel OptimizationReal-Time InferenceRecommendation SystemsDistributed MicroservicesSQL/NoSQL DatabasesCI/CDContainerization
Soft Skills
Technical LeadershipCollaborationMentorshipProblem-SolvingCustomer Orientation
Tools & Technologies
DockerKubernetesKafkaRedisMLOps
Industry Keywords
FintechRegulated IndustriesAgentic SystemsAI-Powered SystemsData Pipelines
Tech Stack
Tools & technologiesCloudDockerJavaKafkaKubernetesMicroservicesNoSQLPythonRedisSQLC++Go
About the role
Key responsibilities & impact- Serve as a technical leader on an agile team, turning complex, ambiguous problems into production-grade AI and agentic systems meeting security, compliance, and regulatory requirements
- Design, build, and ship LLM-powered and agentic features end to end, from shaping solutions with product and design through production coding and post-launch performance and reliability ownership
- Contribute to high-level architecture and detailed design of complex subsystems, emphasizing high availability, scalability, and low latency
- Build and integrate AI capabilities, including LLMs, agents, RAG, orchestration, and tool-use, into distributed, cloud-native services and data pipelines
- Lead code reviews, drive consistent development practices, and champion automated testing and evaluation frameworks for AI systems
- Debug and troubleshoot software and model-related issues, identify defects, and drive remediation
- Mentor engineers, influence the team's technical strategy, and help prioritize initiatives
Requirements
What you’ll need- Bachelor's degree in Computer Science, Information Systems, or equivalent experience
- 8+ years of professional software engineering experience
- Meaningful production experience with LLMs or applied ML systems
- Strong programming skills in Python and proficiency in at least one other object-oriented language (e.g., Java, C/C++, or Go)
- Deep command of data structures, algorithms, and complexity trade-offs
- Strong grasp of ML and GenAI concepts, including Transformers, CNNs, loss functions, bias-variance trade-offs, precision/recall, and model optimization such as INT8/FP8 quantization
- Ability to design large-scale ML systems such as RAG pipelines, real-time inference, and recommendation systems, emphasizing high availability, low latency, and scale
- Proven ability to handle ambiguity, navigate cross-functional conflict, collaborate effectively, and demonstrate technical leadership and mentorship
- Track record of designing, shipping, and operating AI-powered or agentic systems in production
- Strong engineering fundamentals across backend systems, APIs, distributed microservices, data pipelines, and cloud infrastructure
- Knowledge of end-to-end system design, including SQL/NoSQL databases, Kafka, Redis, caching, and low-latency, high-throughput systems
- Experience building and deploying cloud-native applications; familiarity with Docker, Kubernetes, or similar platforms
- Hands-on DevOps/MLOps experience with CI/CD, containerization, monitoring, productionizing, and maintaining solutions
- Fluency with AI-assisted and agentic development workflows and tooling
- Strong sense of ownership, sound technical judgment, and comfort operating with autonomy and ambiguity
- Strong product mindset and customer orientation
- Experience building AI or agentic systems in fintech or other regulated industries (good to have)
- Experience with vector databases, advanced retrieval, and large-scale data pipelines (good to have)
- Deep experience with agentic frameworks and orchestration such as LangChain, LangGraph, or AutoGen (good to have)
Benefits
Comp & perks- Competitive base salaries
- Bonus incentives
- Support for financial well-being and retirement
- Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location)
- Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
- Generous paid parental leave policies (depending on your location)
- Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
- Free and confidential counseling support through our Healthy Minds program
- Career development and training opportunities