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Sympera AI

AI-powered platform for relationship banking

Technical Consultant

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeOntario, CanadaNo salary listed

About the Job

Requirements

  • Have 3 to 7 years of technical implementation experience with hands-on delivery in enterprise or client-facing environments, including at least one deployment through UAT or one data pipeline delivered to production.
  • Build queries and pipelines using SQL, perform data validation and quality checks, and troubleshoot database or data integration issues.
  • Have Linux/Unix and Bash scripting experience, and be able to read and troubleshoot Python, Java, or similar code.
  • Have deployment and automation experience with Git, GitHub, CI/CD, YAML, Helm, and working knowledge of Kubernetes.
  • Have integration experience with XML and JSON configuration, REST APIs, SAML/SSO, and basic networking concepts.
  • Have cloud experience with at least one major platform such as AWS, Azure, or GCP.
  • Use logs, evidence, and root cause analysis to resolve integration, deployment, data, and environment issues.
  • Explain complex technical topics clearly, manage stakeholder expectations, and provide proactive updates on progress, risks, and issues.
  • Manage an assigned workstream end to end, balance multiple priorities, and escalate architecture or scope changes at the appropriate time.
  • Have practical experience using AI tools or LLM APIs to accelerate technical work and understand the importance of validating outputs before integrating them into business processes.

Responsibilities

  • Own technical delivery by leading configuration, deployment, integration, and data pipeline activities for assigned client workstreams from requirements through OAT and production.
  • Translate client business, regulatory, data, and security needs into clear technical specifications and implementation plans.
  • Develop, validate, orchestrate, and deploy SQL- and Python-based pipelines with data quality checks, scheduling, documentation, and operational readiness.
  • Use GitHub, YAML, Helm, Kubernetes, and CI/CD practices to package, configure, and deploy solutions across SaaS and client environments.
  • Use logs and root cause analysis to resolve moderately difficult issues across data, APIs, SAML/SSO, networking, deployment, and application configuration.
  • Plan and support SIT, UAT, OAT, technical reviews, validation, and production deployment while protecting delivery timelines, SLA commitments, and client acceptance.
  • Use AI tools, LLMs, and RAG to accelerate technical workflows, pipeline development, validation, documentation, and troubleshooting, checking outputs for accuracy and suitability.
  • Support model endpoints, data preparation, and AI or LLM API integration through REST endpoints or SDKs, and help monitor deployed AI solutions.
  • Work with client stakeholders, Technical Program Managers, Solution Architects, Data Science, Engineering, and Product Delivery on decisions, risks, and scope.
  • Provide proactive status updates on delivery, dependencies, risks, issues, and technical decisions to project sponsors and senior stakeholders.
  • Share implementation practices and mentor junior consultants while escalating architecture changes and material scope decisions to appropriate senior owners.

Desired Qualifications

  • Hands-on experience with AML, KYC, fraud, sanctions, transaction monitoring, alert management, or other compliance platforms.
  • Experience with Spark, Snowflake, or another enterprise data platform.
  • Experience with pipeline orchestration, scheduling, production monitoring, and data quality frameworks.
  • Exposure to ML model deployment, model endpoints, feature preparation, or monitoring for data drift and model degradation.
  • Experience with GraphQL, microservices, rule engines, or complex enterprise integrations.
  • A cloud certification in AWS, Azure, or GCP.
  • Experience working with global enterprise clients and distributed delivery teams.
  • Understanding of AI model governance, including explainability, auditability, and data privacy in production environments.

About the Company

Sympera AI

AI-powered platform for relationship banking

Sympera AI provides an AI-powered platform for financial institutions that strengthens relationship banking. It helps banks and their relationship managers be more productive and grow client portfolios by offering financial intelligence and sales enablement tools. The platform combines market intelligence with client relationship management so bankers can uncover opportunities, monitor the health of business relationships, and choose effective strategies. This differentiates Sympera AI by offering an integrated solution that pairs data-driven insights with CRM capabilities, aimed at improving service and outcomes for clients. The company’s goal is to redefine relationship banking by using big data and AI to drive business growth and higher client satisfaction for financial providers.

Company size
11-50
Company stage
Seed
Total funding
$10M
Headquarters
New York City, New York
Founded
2024

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