Company Profile :
Our client is a Singapore headquartered company. You will embody their company culture and use your craft and creativity to help them take their operating system to the next level. They are team with decades of wealth management experience, now focused on transforming legacy technology into intelligent, AI-driven solutions. They are looking for someone who loves building products and is curious and passionate about our tech stack.
Duties and Responsibilities :
- Lead end-to-end solution design and technical delivery for bank clients : integrations with CRM, PMS, core banking, market data, and data warehouses
- Run technical pre-sales and discovery workshops with bank stakeholders (IT, InfoSec, Compliance, RMs) to capture requirements and constraints (data residency, connectivity, SLAs)
- Create client-specific deliverables : architecture diagrams, integration specs, API contracts, deployment blueprints (on-prem / hybrid / cloud), and operational runbooks
- Lead PoCs and pilots : scope, timebox, deliver technical artefacts, measure success against acceptance criteria, and iterate with client feedback
- Ensure solutions meet regulatory and bank controls, produce compliance-ready documents for bank review and audit
- Design multi-tenant and per-bank isolation strategies : tenant separation, network segmentation, KMS per-client, and role-based access models
- Define MLOps & ModelOps patterns for production : model packaging, versioning, CI / CD, canary rollouts, drift detection, retraining cadence, and approval gates tailored to each bank’s governance
- Provide professional-service delivery leadership during rollout : cutover planning, data migration strategies, DR / BCP, runbooks, training, and support transition to bank operations or managed service
- Produce cost estimates, TCO models, and risk register for client proposals; engage with procurement and legal to evaluate vendor / cloud constraints
- Mentor internal engineers on bank-grade architecture and delivery best practices; contribute to reusable implementation patterns and onboarding kits for new bank customers
Deliverables in first 6 months (vendor focused) :
Lead PoCs and pilots : scope, timebox, deliver technical artefacts, measure success against acceptance criteria, and iterate with client feedbackEnsure solutions meet regulatory and bank controls, produce compliance-ready documents for bank review and auditDesign multi-tenant and per-bank isolation strategies : tenant separation, network segmentation, KMS per-client, and role-based access modelsDefine MLOps & ModelOps patterns for production : model packaging, versioning, CI / CD, canary rollouts, drift detection, retraining cadence, and approval gates tailored to each bank’s governanceProvide professional-service delivery leadership during rollout : cutover planning, data migration strategies, DR / BCP, runbooks, training, and support transition to bank operations or managed service.Produce cost estimates, TCO models, and risk register for client proposals; engage with procurement and legal to evaluate vendor / cloud constraintsMentor internal engineers on bank-grade architecture and delivery best practices; contribute to reusable implementation patterns and onboarding kits for new bank customersSuccess Metrics / KPIs (for the role) :
PoC → Pilot conversion rate across bank prospects.Time-to-PoC and time-to-pilot (targets set per pipeline)Customer satisfaction for deployments (post-go-live NPS / RM satisfaction)Incidents & escalations : MTTR and number of security / compliance findings post-handover.Reuse of platform patterns : number of banks onboarded using the reusable implementationRequirements
6+ years in software architecture or technical delivery; 3+ years in ML / AI system design and production deploymentsHands-on with cloud-native architectures (AWS / Azure / GCP), containers (Docker), and orchestration (Kubernetes) and experience implementing on-prem / hybrid deploymentsPractical experience with LLMs, RAG, embedding pipelines and vector DBs, and designing explainability and auditability into AI outputsStrong client-facing skills : running discovery workshops, producing SOW-level technical designs, and managing technical escalations6+ years in software architecture or technical delivery; 3+ years in ML / AI system design and production deploymentsHands-on with cloud-native architectures (AWS / Azure / GCP), containers (Docker), and orchestration (Kubernetes) and experience implementing on-prem / hybrid deploymentsPractical experience with LLMs, RAG, embedding pipelines and vector DBs, and designing explainability and auditability into AI outputsStrong client-facing skills : running discovery workshops, producing SOW-level technical designs, and managing technical escalationsAdvantageous Skills :
Prior experience implementing RM / Wealth Management tooling or CRM / PMS integrations for banksCertifications : AWS / Azure / GCP Architect, CISSP / CISM, TOGAF, or Project Management certificationExperience operating a SaaS platform with per-client isolation or running managed services for banksProven experience delivering enterprise implementations for banks or regulated financial institutions (vendor / consulting or fintech role preferred)Degree in Computer Science / Engineering / Data Science or equivalent experienceFamiliarity with banking regulations and data privacy — experience producing compliance artefacts is a plusFamiliar with MLOps tools and CI / CD for models (Airflow, MLflow, Kubeflow or equivalents), infra-as-code (Terraform / ARM), and config management.