qode.world

Security Engineer

• Lead and oversee the management, configuration, and tuning of security detection and response platforms, including:
• SIEM (e.g., Splunk, PANW, or Azure Sentinel)
• EDR/XDR (e.g., CrowdStrike, SentinelOne, Microsoft Defender)
• SOAR automation platforms
• Network IDS/IPS, NDR, and threat intelligence platforms (TIPs)
• Ensure all detection tools are integrated for end-to-end visibility across endpoints, cloud environments, and production systems
• Define standards for log collection, parsing, and correlation to enhance alert accuracy and reduce false positives
• Drive continuous tuning of detection rules, signatures, and use cases to align with MITRE ATT&CK and emerging threats
• Collaborate with IT and Engineering teams to ensure security telemetry is fully integrated into cloud and CI/CD environments
• Oversee threat hunting, alert triage, and incident response playbook execution across the security stack
• Partner with DevOps and infrastructure teams to embed security monitoring hooks into hybrid environments and new deployments
• Design and conduct controlled adversary emulation exercises to test detection and response capabilities
• Execute attack chains including phishing, privilege escalation, persistence, and lateral movement using real-world TTPs
• Develop and maintain custom adversary scripts and payloads to simulate targeted threats
• Provide detailed post-exercise reports with actionable defensive improvement recommendations
• Collaborate with Blue Team engineers to operationalize detections based on Red Team findings
• Lead or co-lead major incident response efforts, coordinating containment, investigation, and recovery
• Build and maintain detailed incident response runbooks, integrating lessons learned from purple team exercises
• Conduct root cause analysis and lead retrospectives that drive measurable improvements in detection and resilience
• Integrate threat intelligence and forensic insights into detection content and defensive playbooks.
• Plan and execute adversarial simulations that validate threat detection, alert fidelity, and incident response readiness
• Develop the roadmap for continuous improvement of detection coverage, response automation, and control validation
• Serve as a technical escalation point for complex investigations, guiding both Red and Blue Team staff
• Translate technical results into executive-level insights that demonstrate risk reduction and readiness improvement

Cybersecurity Lead

Architect

• Lead the architecture, design, implementation, and support of enterprise CIAM solutions using Ping Identity products.
• Own end-to-end solution design for customer authentication, federation, authorization, and directory integration use cases.
• Design scalable and secure authentication platforms capable of supporting large user populations and high transaction volumes.
• Implement and optimize SSO, MFA, OAuth, OIDC, and federation flows for enterprise and customer-facing applications.
• Drive integration with downstream applications, identity providers, APIs, directories, and security infrastructure.
• Lead production issue resolution for complex authentication, federation, token, certificate, and directory-related problems.
• Collaborate with infrastructure, network, security, application, and DevOps teams to ensure resilient and secure identity services.
• Define engineering standards, deployment patterns, operational runbooks, and best practices for CIAM platform support.
• Provide technical leadership to engineering teams, review solution designs, and mentor junior team members.
• Support modernization initiatives including cloud adoption, automation, and observability for identity platforms.

Senior CIAM Architect

Scrum Master

• Facilitate Agile ceremonies including sprint planning, daily stand-ups, retrospectives, and backlog grooming.
• Coach teams on Scrum principles, Agile best practices, and continuous improvement.
• Work closely with Product Owners, Data Analysts, and Engineering teams to align delivery with business priorities.
• Remove blockers and resolve dependencies to ensure smooth sprint execution.
• Track sprint progress, team velocity, and key performance indicators.
• Support the delivery of data analytics initiatives, including dashboards, reporting frameworks, and business intelligence solutions.
• Ensure effective collaboration between business stakeholders and technical teams.
• Drive transparency in project status, risks, and delivery timelines.
• Foster a high-performing and accountable Agile team culture.

Technical Program Manager

• The Technical Program Manager (TPM) will lead complex, multi‑team technology initiatives across trading, investment, advisor‑facing, and data‑driven platforms.
• Oversee roadmap execution, cross‑functional alignment, vendor and platform integration, and regulatory‑aligned delivery.
• Ensure that platform enhancements, data flows, and application interfaces are designed, integrated, and delivered with reliability, scalability, and compliance in mind.
• Establish program structure, milestones, RAID logs, and reporting for multi‑workstream initiatives.
• Coordinate engineering, product, QA, architecture, operations, and compliance teams.
• Ensure solution design, system integration, and implementation align with business, technical, and regulatory requirements.
• Drive end‑to‑end delivery of platform enhancements, trading workflows, API‑driven integrations, data pipelines, and advisor‑facing capabilities.
• Oversee integration of internal and external applications using REST APIs, microservices, event‑driven patterns, and secure data‑exchange frameworks.
• Provide clear, data‑driven executive reporting to senior leadership.
• Translate complex technical concepts—including API architecture, integration dependencies, and system interoperability—into business‑aligned communication.
• Lead programs involving trading platforms, portfolio management systems, wealth & advisory platforms, market data integrations, and regulatory & compliance‑driven initiatives.

Solutions Engineer

• Architect end-to-end AI Agent solutions leveraging LLM and Agentic frameworks (LangChain, AutoGen, CrewAI) integrated with enterprise systems.
• Design API-first and event-driven integration architectures ensuring reliability, scalability, and low-latency across services.
• Define governance frameworks for AI agents including access control, audit trails, policy enforcement, and responsible AI guardrails.
• Establish observability standards using LaunchDarkly, feature flagging strategies, and DevOps pipelines for AI-driven systems.
• Collaborate with stakeholders across Engineering, Data, Product, and Risk to align architecture decisions with business outcomes.
• Create and maintain Technical Solution Architecture documentation, including architecture decision records (ADRs), data flows, and system diagrams.
• Evaluate and recommend emerging AI tools, LLM providers, and orchestration platforms for enterprise adoption.
• Provide technical leadership and mentoring to engineering squads implementing agentic solutions.

Solution Architect

Artificial Intelligence

• Design, develop, and deploy AI Agent workflows using LLM-based orchestration frameworks (LangChain, AutoGen, CrewAI, or similar).
• Integrate LaunchDarkly for feature flagging, progressive rollouts, and experimentation across AI-enabled features.
• Implement comprehensive telemetry, logging, distributed tracing, and monitoring for AI agent systems.
• Build and maintain A/B testing and experimentation frameworks to evaluate agent performance and model outputs.
• Develop REST and event-driven integrations to connect AI agents with enterprise data sources and downstream systems.
• Author technical documentation including agent design specs, integration guides, and architecture deliverables.
• Participate in sprint ceremonies, contribute to backlog grooming, and deliver iteratively within an Agile framework.
• Support incident response, root-cause analysis, and continuous improvement for production AI systems.

AI Engineer

Data Analyst

• Join the growing team at Austin, TX as a Data Analyst – Wealth Management
• Write sophisticated SQL queries and analyze large datasets
• Define business logic and validate data across wealth management systems
• Partner with investment teams, operations, and technology stakeholders

Data Analyst – Wealth Management

Data Engineer

• 8–10 years in Data Engineering and Data Analysis.
• Strong hands-on experience in Informatica PowerCenter/IDQ for ETL design, development, and optimization.
• Advanced skills in PySpark for large-scale data processing, transformation, and analytics.
• Solid working knowledge of Hadoop technologies (HDFS, Hive, Sqoop, MapReduce).
• Proficiency in Python and Kafka for streaming and batch data pipelines.
• Strong understanding of database concepts, data design, data modeling, and ETL workflows.
• Experience in analyzing, designing, and coding ETL programs including data extraction, ingestion, quality checks, normalization, and loading.
• Hands-on experience with Agile methodology and Jira for project delivery.
• Proven ability in client-facing roles with strong communication and leadership skills to coordinate across SDLC.
• Exposure to AWS data components and analytics.
• Familiarity with machine learning models and AI concepts.
• Experience with data modeling tools such as Erwin.

Senior Data Engineer

Backend Engineer

• Design, develop, and maintain Java-based web applications using Spring Boot and related frameworks
• Build and consume RESTful APIs and, where applicable, GraphQL endpoints
• Deploy, monitor, and maintain applications using AWS services such as EC2, S3, Lambda, RDS, and SQS
• Collaborate with front-end teams working on Angular-based UIs and JSP pages
• Develop and optimize data access layers using Hibernate/JPA with relational databases (Oracle, MySQL, SQL Server)
• Write clean, maintainable, and testable code with proper unit testing using JUnit and Mockito
• Participate in code reviews, architectural discussions, and technical design decisions
• Work within CI/CD pipelines using tools like Jenkins, Maven, and Git
• Actively contribute to Agile ceremonies including daily stand-ups, sprint planning, and retrospectives

Senior Java Developer

• Build and optimize large-scale data pipelines
• Work with wealth management data including positions, transactions, and accounts
• Utilize Databricks for data engineering tasks
• Collaborate with teams on AI tool implementation in daily work

Financial Planning and Analysis

• Support as a key point of contact for advisor inquiries, escalations, and ongoing service needs
• Identify and help resolve advisor pain points related to platform functionality, data quality, and reporting
• Develop trusted relationships with advisors to ensure high satisfaction, adoption, and retention
• Triage and route service issues across data, operations, sales, and the platform implementation team with urgency and clarity
• Act as the connective tissue between advisors and internal teams — translating advisor needs into actionable tickets and resolution paths
• Track open issues and ensure timely resolution; maintain accountability across stakeholders
• Execute on the established service model for advisor-facing support, contributing to the refinement of intake, triage, escalation, and resolution workflows
• Contribute to playbooks, FAQs, and self-service resources to reduce recurring issues and improve advisor independence
• Track and report on service KPIs including response times, resolution rates, and advisor satisfaction
• Support advisors in navigating client and advisor portal features, reporting tools, and data integrations
• Identify recurring data quality issues and partner with the data and operations teams to implement upstream fixes
• Stay current on platform product updates and ensure advisors are informed of changes that affect their workflows

Service Consultant – Financial Advisor Technology Platform

• Explore and profile large, complex financial datasets to understand structure, lineage, gaps, and anomalies across custodian, portfolio, and transaction data.
• Identify data relationships, patterns, and inconsistencies across source systems to inform data mapping, transformation logic, and business rules.
• Conduct deep-dive analysis on wealth management data — including positions, returns, benchmarks, fees, and cash flows — to validate completeness and accuracy.
• Document data dictionaries, field definitions, and business logic for use by both technical and non-technical teams.
• Investigate data quality issues end-to-end, trace root causes across source systems, and recommend remediation approaches.
• Engage directly with business stakeholders — advisors, portfolio managers, operations, and compliance — to gather, analyze, and document functional data requirements.
• Translate business requirements into precise data logic, transformation rules, and acceptance criteria for downstream development and reporting.
• Define and formalize calculation logic for KPIs such as AUM, performance returns, fee schedules, and client segmentation.
• Review and validate business logic implemented in pipelines, data models, and reports to ensure alignment with requirements.
• Act as a bridge between business teams and technology, ensuring data solutions are grounded in real operational needs.
• Write complex SQL queries — including CTEs, window functions, and aggregations — to analyze datasets, build reusable logic, and support reporting and validation needs.
• Validate pipeline outputs by querying source and target systems, reconciling counts, amounts, and key metrics to confirm data integrity.
• Develop test cases and validation scripts to verify transformation logic, business rules, and data completeness after pipeline runs.
• Use Python and/or Databricks notebooks for ad hoc data analysis, profiling, and validation where scale or complexity requires it.
• Collaborate with engineering teams to review transformation logic, flag discrepancies, and verify that implemented pipelines match documented requirements.
• Develop and maintain dashboards, reports, and KPI frameworks to support advisors, portfolio managers, and leadership.
• Support client segmentation, performance reporting, AUM analysis, and investment strategy analysis.
• Translate complex financial data findings into clear, concise narratives and recommendations for non-technical audiences.
• Ensure all reporting outputs comply with financial regulations and internal data governance standards.

Senior Data Analyst – Wealth Management

Product Manager

• Product Strategy — Define product vision, roadmap, and long‑term direction aligned with business objectives.
• Backlog Ownership — Manage, refine, and prioritize the product backlog to ensure delivery of high‑value features.
• Agile Execution — Lead Agile ceremonies including sprint planning, grooming, reviews, and retrospectives.
• Stakeholder Alignment — Partner with business, technology, operations, and compliance teams to ensure alignment and clarity.
• Requirements Definition — Translate business needs into detailed user stories, acceptance criteria, and functional requirements.
• Financial Technology Expertise — Support initiatives across any financial domain such as payments, trading, lending, digital banking, risk, compliance, or investment operations.
• Delivery Oversight — Ensure timely delivery of product increments and remove impediments in partnership with engineering.
• Data‑Driven Decisioning — Use KPIs, analytics, and customer insights to guide prioritization and continuous improvement.
• Regulatory & Compliance Awareness — Ensure product solutions adhere to industry regulations and security standards.

Senior Product Owner

Systems Engineer

• Business Requirements — Lead discovery, documentation, and clarification of business needs.
• Data Analysis — Explore, validate, and interpret datasets to support program governance and operational decision‑making.
• Visualization & Insights — Build dashboards and analytical outputs using Power BI or Tableau.
• Stakeholder Communication — Present insights clearly to senior leaders and cross‑functional partners.
• Cross‑Functional Alignment — Work with ALM, Practice Management, Legal, Customer Relations, and Back Office teams to ensure consistent understanding of data and processes.
• Domain Interpretation — Apply financial‑services or wealth‑management knowledge to contextualize data and business workflows.

Senior Business Systems Analyst

Risk

• Oversee fraud management, risk control, and compliance operations.
• Define risk appetites, build and optimize risk models, and ensure trademark protection.
• Manage a team of specialists to mitigate fraud/security/financial/compliance risks on Platform Ecommerce.
• Actively identify signs of fraud and implement countermeasures promptly.
• Utilize data-driven approaches to build, evaluate, and optimize rule-based models or risk scoring/behavioral models.
• Leverage data and analytical tools to detect fraud patterns and propose actionable preventive measures.
• Establish a framework for audits to review the effectiveness of models, processes, and policies.
• Detect and mitigate trademark/IP infringement issues on E-commerce platforms.
• Work with cross-functional teams to resolve violations and enforce compliance.
• Lead projects related to Fraud, Risk, or Compliance when expanding into new products or markets.
• Act as an internal advisor on risk management and fraud prevention strategies.