Ai/ml senior engineer

Key Responsibilities

Lead Agile ceremonies, including Sprint Planning, Grooming, and Estimation, with cross-functional teams comprising engineers, product managers, and data scientists to scope AI/ML, LLMOps, payment processing, and analytics solutions.

Gather, analyze, and translate complex business requirements from stakeholders into scalable technical architectures aligned with enterprise goals.

Define user journeys, data contracts, redline documents, and cross-platform integration requirements across web, mobile, backend, and payment systems.

Architect enterprise-grade AI/ML platforms across AWS (e.g., SageMaker, Bedrock, Redshift) and GCP (e.g., Vertex AI, BigQuery) to support the full ML lifecycle.

Design and implement scalable payment processing solutions, integrating payment gateways, payment APIs, and third-party financial service providers.

Develop and integrate payment workflows covering authorization, capture, settlement, refunds, voids, recurring payments, and transaction reconciliation.

Work with payment technologies and protocols, including REST APIs, webhooks, tokenization, and secure transaction processing, ensuring reliability and scalability.

Ensure secure payment integrations and compliance with industry standards such as PCI DSS, along with appropriate data encryption, fraud prevention, and transaction monitoring mechanisms.

Leverage AI/ML capabilities for payment fraud detection, anomaly detection, transaction risk assessment, and intelligent payment analytics.

Build secure and production-ready LLMOps pipelines, including data preprocessing, RAG (Retrieval-Augmented Generation), fine-tuning, evaluation, deployment, and monitoring.

Deploy and optimize large language models (e.g., GPT-4, Claude, Llama 3) using AWS Bedrock, GCP Vertex AI, and custom APIs.

Integrate vector databases (e.g., Pinecone, FAISS, Chroma) and frameworks such as LangChain or LlamaIndex to support contextualized GenAI applications.

Design and implement microservices for GenAI and payment processing use cases using Python (FastAPI, Flask), Node.js, and deploy via ECS Fargate and GKE.

Build and operationalize real-time and batch data pipelines using AWS Glue, EMR, Kinesis, GCP Dataflow, and Pub/Sub for analytics, payment processing, and ML workflows.

Integrate and govern data lakes and federated marts to support self-service analytics and compliance needs via tools such as Looker, Tableau, and Athena.

Implement and manage CI/CD pipelines using GitHub Actions, Jenkins, and AWS/GCP DevOps tools to support model deployment and containerized workflows.

Use Infrastructure as Code tools such as Terraform, AWS CDK, and Helm to provision and manage scalable cloud resources.

Apply DevSecOps practices, including IAM, VPC segmentation, KMS, and compliance automation, to meet regulatory requirements (SOX, GDPR, HIPAA, and PCI DSS).

Conduct comprehensive testing (unit, integration, load, and payment transaction testing) and monitor production performance using tools such as PyTest, Postman, Prometheus, CloudWatch, and Grafana.

Establish model observability and monitoring frameworks (e.g., LangWatch, WhyLabs, Weights & Biases) to track performance, drift, and data quality.

Mentor junior architects, ML engineers, and developers on best practices in MLOps, LLM architecture, payment integrations, and secure cloud deployments.

Maintain comprehensive technical documentation, including architecture diagrams, SOPs, API specifications, and Confluence articles.

Lead initiatives in GenAI innovation, payment technology modernization, observability tooling, and Responsible AI governance while ensuring platform security and compliance.

Preferred Payment Processing Experience:

• Hands-on experience integrating payment gateways such as Stripe, Adyen, Worldpay, PayPal, Braintree, or similar platforms.
• Strong understanding of payment lifecycle, transaction processing, authorization, settlement, refunds, chargebacks, and reconciliation.
• Experience with payment APIs, webhooks, tokenization, fraud detection, and PCI DSS compliance.

This is a remote position.