Senior AI Engineer I
American Express · Posted Oct 7
Banking, credit card, payment network, and travel services
Bengaluru, KA, IndiaFull-timeHybridLead/Staff8+ years₹40.0L–₹65.0L yearly100+ applicants
BankingPaymentsCredit CardsFinancial ServicesPublic Company
Full time
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About the role
American Express is building next-generation Agentic AI platforms, large-scale data and AI systems, and cloud-native engineering solutions that power intelligent business processes across the enterprise. The team works across GenAI, LangGraph workflow orchestration, distributed data engineering on Google Cloud Platform, MLOps, and responsible AI governance. This role leads the design, development, deployment, and scaling of production-grade Agentic AI and RAG systems, and provides technical direction and mentorship across AI engineering initiatives.
What you will do
- Design, develop, and deploy enterprise-scale Agentic AI applications using LangGraph, LangChain, and modern LLM frameworks.
- Build and optimize multi-agent workflows including routing, planning, reasoning, memory, validation, and execution agents.
- Develop production-grade agent orchestration frameworks capable of handling complex business processes.
- Implement workflow state management, checkpointing, human-in-the-loop controls, and failure recovery mechanisms.
- Design intelligent agent collaboration patterns including supervisor-agent, planner-executor, and hierarchical agent architectures.
- Create reusable AI skills, tools, prompts, and workflow libraries that accelerate enterprise AI adoption.
- Build scalable AI services and APIs deployed on GKE (Google Kubernetes Engine).
- Design containerized AI workloads using Kubernetes, Helm, Docker, and GitOps deployment practices.
- Implement CI/CD pipelines for Agentic AI and GenAI applications.
- Optimize inference latency, throughput, resource utilization, and operational costs across AI workloads.
- Support production deployment, monitoring, observability, and incident management for AI systems.
- Design resilient and highly available AI infrastructure supporting enterprise SLAs.
- Build distributed data pipelines using Apache Beam, Spark, Dataproc, Dataflow, and BigQuery.
- Design batch and streaming ingestion frameworks using Pub/Sub and event-driven architectures.
- Develop scalable ETL/ELT pipelines supporting AI and analytics workloads.
- Implement enterprise data processing frameworks for structured, semi-structured, and unstructured data.
- Build data quality, lineage, metadata, and governance capabilities across AI pipelines.
- Optimize BigQuery and storage architectures for performance and cost efficiency.
- Design and implement Retrieval Augmented Generation (RAG) platforms.
- Build vector search and semantic retrieval solutions using enterprise knowledge repositories.
- Develop document ingestion, indexing, chunking, embedding, and retrieval pipelines.
- Implement hybrid search architectures combining vector, keyword, and graph-based retrieval capabilities.
- Build knowledge graphs and context-management systems supporting intelligent agents.
- Design AI systems capable of processing millions of records and large-scale enterprise datasets.
- Improve workflow reliability through distributed execution, workload partitioning, and fault-tolerant designs.
- Implement asynchronous processing using Pub/Sub, event-driven architectures, and worker-based execution models.
- Build performance monitoring, tracing, and observability frameworks using OpenTelemetry and cloud-native monitoring tools.
- Conduct load testing, performance tuning, and capacity planning activities.
- Implement model governance, auditability, explainability, and compliance controls.
- Develop automated validation and confidence-scoring frameworks for GenAI outputs.
- Establish evaluation pipelines for model quality, hallucination detection, and business-rule validation.
- Support secure and compliant use of enterprise data in AI systems.
- Partner with governance and risk teams to align AI solutions with enterprise standards.
- Lead architecture reviews and provide technical direction across AI engineering initiatives.
- Mentor junior engineers and establish engineering best practices.
- Drive innovation in Agentic AI, GenAI, LLMOps, and cloud-native engineering.
- Collaborate with product, business, and enterprise architecture teams to deliver strategic AI capabilities.
- Contribute to enterprise AI platforms, reusable frameworks, and long-term technology roadmaps.
Skills used in this role
PythonLangGraphLangChainCrewAIAutoGenGoogle CloudGKEBigQueryDataflowDataprocPub/SubApache BeamSparkKubernetesDockerHelmGitOpsCI/CDPostgreSQLRedisNoSQLOpenTelemetryRAGVector SearchKnowledge Graph
What the employer is looking for
- Bachelor's or master’s degree in computer science,Engineering, or related field.
- 8+ years of software engineering experience with AI/ML or GenAI engineering.
- Strong experience building production systems in Python.
- Hands-on experience with LangGraph, LangChain, CrewAI, AutoGen, or equivalent agent orchestration frameworks.
- Experience deploying applications on Google Cloud Platform (GCP).
- Strong background in data engineering, distributed systems, and large-scale data processing.
- Experience with BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, and GKE.
- Experience building RAG, Vector Search, and Knowledge Graph solutions.
- Experience with Kubernetes, Docker, CI/CD, and infrastructure automation.
- Strong understanding of software design patterns, distributed architectures, and microservices.
- Experience with PostgreSQL, Redis, and NoSQL technologies.
- Knowledge of observability, monitoring, and production support processes.
Benefits and support
- 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
About American Express
American Express Company is a globally recognized multinational financial services corporation specializing in payment cards, travel-related services, and network banking. Founded in 1850, the company provides charge and credit cards, expense management products, and merchant services to consumers, small businesses, and large corporations worldwide. It operates a proprietary payments network known for its premium customer engagement and lifestyle rewards programs.
- Industry
- Banking
- Company size
- 76800 employees
- Founded
- 1850-03-18
- Location
- New York City, New York, USA
- Funding stage
- Public Company
Leadership
SJ
Stephen J. Squeri
Chairman and Chief Executive Officer
CL
Christophe Le Caillec
Chief Financial Officer
RR
Ravi Radhakrishnan
Chief Information Officer and Executive Vice President
MR
Monique R. Herena
Chief Colleague Experience Officer
ER
Elizabeth Rutledge
Chief Marketing Officer
Recent coverage
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