{"id":737422,"url":"https://alion.io/job/multibankgroup-senior-ai-architect","title":"Senior AI Architect","company":{"id":450222,"name":"Multi Bank Group","domain":"multibankgroup.com","url":"https://alion.io/company/multibankgroup","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"C","score":58,"open_postings":13,"ghost_share":0.692,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-05T05:54:30Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Dubai, United Arab Emirates"],"countries":["AE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":56000,"max_usd":129000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1279},"experience_years_min":15,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon EC2","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon EventBridge","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"Apache Kafka","optional":false},{"name":"API Gateway","optional":false},{"name":"ArgoCD","optional":false},{"name":"Arize Phoenix","optional":false},{"name":"Atlantis","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Fargate","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Azure","optional":false},{"name":"BentoML","optional":false},{"name":"CI/CD","optional":false},{"name":"ClearML","optional":false},{"name":"CloudFormation","optional":false},{"name":"Dagster","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"Draw.io","optional":false},{"name":"DynamoDB","optional":false},{"name":"Evidently AI","optional":false},{"name":"FastAPI","optional":false},{"name":"Feast","optional":false},{"name":"Feature Store","optional":false},{"name":"Firebase","optional":false},{"name":"Fivetran","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"GDPR","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Grafana","optional":false},{"name":"GraphQL","optional":false},{"name":"Great Expectations","optional":false},{"name":"gRPC","optional":false},{"name":"HashiCorp Vault","optional":false},{"name":"Helm","optional":false},{"name":"Hugging Face","optional":false},{"name":"IAM","optional":false},{"name":"ISO 27001","optional":false},{"name":"Istio","optional":false},{"name":"Karpenter","optional":false},{"name":"Kong","optional":false},{"name":"KServe","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"Kustomize","optional":false},{"name":"LightGBM","optional":false},{"name":"Metabase","optional":false},{"name":"MLFlow","optional":false},{"name":"NIST AI RMF","optional":false},{"name":"OpenAI","optional":false},{"name":"Pandas","optional":false},{"name":"PEFT","optional":false},{"name":"Polars","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prefect","optional":false},{"name":"Pulumi","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Ray","optional":false},{"name":"Ray Serve","optional":false},{"name":"Redis","optional":false},{"name":"Rest API","optional":false},{"name":"Scala","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Seldon Core","optional":false},{"name":"Service Mesh","optional":false},{"name":"SHAP","optional":false},{"name":"Snowflake","optional":false},{"name":"SOC 2","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Terraform","optional":false},{"name":"Terragrunt","optional":false},{"name":"Transformers","optional":false},{"name":"Weights & Biases","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-06-02T12:47:15Z","employer_posted_date":"2026-06-02","last_verified_at":"2026-11-05T07:49:54Z","board_verified":true,"closed_at":null,"days_open":156,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":155},"description":"Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.\nJoin our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.\nRole Overview\nWe are seeking a Senior AI Architect to design, build, and scale the AI and data platform that the organization's AI products will run on. This is a hands-on, founding technical position. The Senior AI Architect will produce architecture designs, write production code, build data pipelines, and set the engineering standards the broader AI team will follow. The role requires rare technical breadth: deep data engineering foundations, strong software engineering discipline, AI and ML systems experience, cloud infrastructure fluency, and the architectural vision to make it all coherent at enterprise scale.\nKey Responsibilities\nDesign and build the end-to-end AI platform architecture, covering data ingestion, feature engineering, model training, serving, monitoring, and retraining as a coherent, maintainable production system\n\nDesign the data lakehouse architecture on AWS using Delta Lake or Apache Iceberg with Databricks as the primary compute layer, and build batch and streaming data pipelines using PySpark, AWS Glue, and Kafka\n\nArchitect and implement a feature store with online and offline stores, point-in-time joins, and feature versioning\n\nOwn cloud infrastructure architecture for all AI and data workloads on AWS, including multi-account strategy, EKS cluster design, GPU compute, storage, and cost governance\n\nBuild and own the MLOps platform covering experiment tracking, training pipeline automation, model packaging and deployment standards, CI/CD for ML, and model monitoring with drift detection\n\nDesign the AI services layer, including reusable inference APIs, model serving infrastructure, and API gateway configuration with authentication, rate limiting, and cost attribution\n\nIntegrate AI capabilities into the organization's products and business systems using event-driven and API-based patterns\n\nEmbed security and compliance into every layer of the AI platform, including network security, IAM, PII handling, secrets management, and audit logging\n\nAct as the senior technical authority for the AI Initiative, setting engineering standards, mentoring engineers, and leading technical decisions\n\nProduce and maintain architecture documentation including C4 diagrams, Architecture Decision Records, and system integration maps\n\nRequirements\n15 or more years of experience spanning data engineering, software engineering, and AI/ML systems, with at least 3 to 5 years in a senior architecture role\n\nDemonstrable record of building and shipping production AI systems end-to-end, not solely designing them\n\nDeep hands-on data engineering background including production data pipelines, data lakehouses, and feature stores\n\nExpert-level AWS skills across multi-service architecture design and build; GCP or Azure familiarity is beneficial\n\nStrong software engineering discipline with production-quality Python and SQL, and solid understanding of distributed systems and API design\n\nDeep understanding of the AI and ML model lifecycle and the infrastructure required to support it at production scale\n\nExperience in high-growth product companies, scale-ups, or enterprise AI teams where significant technical decisions were owned\n\nSecurity-conscious approach as a default, with experience embedding data privacy and compliance requirements into architecture\n\nStrong written and verbal communication, including the ability to produce clear architecture documentation and present to senior leadership\n\nExperience leading or significantly contributing to technical team building, including mentoring and setting engineering standards\n\nFintech experience is preferred\n\nTechnical Skills\nData Engineering and Platform: Python (primary), SQL, Scala, Bash; Apache Spark (PySpark), AWS Glue, dbt, Pandas, Polars; Apache Kafka (AWS MSK), AWS Kinesis, AWS EventBridge, Flink; Delta Lake, Apache Iceberg, AWS S3, Databricks (Unity Catalog); AWS Redshift, Databricks SQL, Snowflake; Feast, AWS SageMaker Feature Store, Tecton; Great Expectations, dbt tests, Soda Core; OpenMetadata, Apache Atlas; Metabase, Redash; Apache Airflow (Astronomer), Dagster, Prefect\n\nAI and ML Systems: PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM; AWS SageMaker Training, Kubeflow, Ray Train; BentoML, Seldon Core, Ray Serve, FastAPI, KServe; MLflow, Weights and Biases, ClearML; Evidently AI, Arize AI, WhyLabs; GitHub Actions, DVC, Great Expectations; Hugging Face (Transformers, Datasets, Evaluate, PEFT)\n\nCloud and Infrastructure (AWS Primary): EKS (Karpenter), EC2 (G5, P4d GPU instances), SageMaker, Lambda, Fargate; S3, FSx for Lustre, ElastiCache (Redis), DynamoDB, RDS (PostgreSQL); SageMaker Pipelines, Feature Store, Model Registry, Bedrock, Comprehend, Textract; VPC, Transit Gateway, PrivateLink, Route 53, CloudFront, WAF; IAM (IRSA), Secrets Manager, KMS, Macie, GuardDuty, Security Hub, CloudTrail; Terraform, Terragrunt, CloudFormation, Pulumi; ArgoCD, Flux, Atlantis; Azure ML, Azure Databricks, Azure OpenAI Service (secondary)\n\nAPI, Integration and Solution Architecture: FastAPI, gRPC, REST (OpenAPI 3.1), GraphQL; Kong, AWS API Gateway, Istio (service mesh, mTLS); Docker, Kubernetes (Helm, Kustomize); C4 Model (Structurizr), ADRs, draw.io, Lucidchart; AWS Cost Explorer, Grafana cost dashboards, per-product token attribution\n\nThird-Party Data Integrations: Segment, Amplitude, Adjust, Firebase, MoEngage, JourneyFi, Funnel, Debezium, AWS DMS, Fivetran\n\nSecurity and Compliance: OAuth 2.0, JWT, AWS Cognito, mTLS, AWS SSO; AWS Secrets Manager (auto-rotation), HashiCorp Vault; Microsoft Presidio (PII detection), AWS Macie, field-level KMS encryption; NIST AI RMF, GDPR, ISO 27001, SOC 2; Model cards, Fairlearn (bias evaluation), SHAP (explainability), audit logging\n\nWhy Join Us?\nWork with one of the world’s leading financial derivatives institutions.\n\nCompetitive salary plus performance-based incentives.\n\nAccess to a dynamic, international, and fast-growing environment.\n\nStrong opportunities for career progression within a global financial group.\n\nBe part of a business committed to innovation, excellence, and long-term growth.\n\nBecome part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.\nMultiBank Group is an equal opportunity employer. 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