aKUBE

Full-stack Engineer

• Build API gateways, wrappers, and middleware for AI agents.
• Create secure access patterns for tools, metadata, and content systems.
• Build agentic workflows for mastering, localization, and delivery.
• Implement tracing, audit logging, governance, approvals, and fallback paths.
• Convert AI prototypes into production microservices.
• Build event-driven services and reliable APIs.
• Lead design reviews and mentor engineers.

Staff Software Engineer – AI Workflow, Agentic Platforms

• Build AI-powered full stack applications from frontend to backend
• Develop and integrate LLM workflows, RAG pipelines, and AI automation features
• Design scalable APIs, microservices, and cloud-native services
• Build responsive UI using React and Next.js
• Develop backend services using Python, Node.js, or Go
• Deploy and maintain applications in AWS environments
• Build distributed systems and large-scale data pipelines
• Collaborate with product, design, and data teams to deliver new features
• Participate in architecture discussions and platform design decisions
• Maintain production reliability through monitoring, logging, and automation
• Support on-call activities and operational improvements
• Mentor engineers through code reviews and technical guidance

Senior Full Stack Engineer – AI, Emerging Technology

Frontend Engineer

• Build and enhance front-end applications using React and TypeScript.
• Revamp and modernize existing UI experiences for internal high-visibility applications.
• Develop new front-end capabilities for election and analytics-focused platforms.
• Collaborate with UX designers, product managers, and engineering teams to deliver scalable user experiences.
• Integrate front-end applications with AWS services, REST APIs, GraphQL APIs, and streaming data services.
• Improve usability, search, navigation, and workflow efficiency across applications.
• Write clean, maintainable, and scalable production-ready code.
• Participate in testing, deployment, troubleshooting, monitoring, and optimization activities.
• Support rapid development timelines and work independently with minimal oversight.

Front-End Engineer, React, AWS

Data Engineer

• Migrate existing Azure Data Factory pipelines into native Snowflake solutions
• Analyze existing ADF pipeline logic and replicate workflows using Snowpark and Python
• Build native Snowflake pipelines using Snowpark libraries, Tasks, Streams, and SQL transformations
• Develop Python scripts and scheduled jobs directly inside Snowflake
• Optimize Snowflake warehouse sizing, compute usage, and job performance
• Support the transition from analytics-focused workflows into a scalable enterprise data warehouse platform
• Build and support Bronze, Silver, and Gold medallion data layers
• Join and transform data from multiple systems for reporting, KPIs, and analytics
• Work from clearly defined technical requirements and task assignments from engineering leadership
• Ensure secure, scalable, and performant Snowflake implementations
• Use AI-assisted development tools such as Cursor or Copilot to accelerate engineering delivery

Senior Snowflake Data Engineer – Snowpark, ADF Migration

Artificial Intelligence

• Migrate workflows from Moveworks to the Serval platform.
• Translate existing business processes into automated AI-driven workflows.
• Analyze and redesign legacy workflows for the new platform.
• Build, configure, and optimize orchestrations within Serval.
• Integrate APIs and enterprise systems into workflow automations.
• Work closely with business stakeholders to gather requirements and convert them into scalable technical solutions.
• Use AI-assisted development tools to rapidly prototype and implement workflows.
• Support testing, troubleshooting, and optimization of orchestrated processes.

AI Orchestration Engineer – Moveworks to Serval Migration

Architect

• Build and support Databricks pipelines for new data source ingestion.
• Design and develop Bronze, Silver, and Gold data layers.
• Optimize Delta Lake tables, queries, and platform performance.
• Debug Genie Spaces and improve natural language query response quality.
• Tune underlying SQL and data models used by Genie Spaces.
• Support short-term delivery needs across the Databricks platform.

Databricks Engineer – Genie Spaces, Medallion Architecture

• Design and build large-scale data pipelines for ingestion and transformation
• Develop ETL and ELT frameworks using Databricks and Spark
• Optimize SQL queries and improve data performance
• Build and maintain scalable data models across lakehouse platforms
• Lead data migration efforts across systems and environments
• Implement orchestration for reliable data workflows
• Monitor data pipelines and resolve production issues
• Ensure governance, data quality, and observability across platforms

Senior Data Engineer – Databricks

Robotics

• Lead discovery and solutioning for new automation opportunities with sales teams
• Define scope, deliverables, timelines, and budgets for BPA projects
• Own client communication with senior stakeholders and drive alignment
• Oversee end to end delivery of automation programs from initiation to closure
• Establish standardized methodologies, reusable components, and best practices
• Monitor project outcomes and drive continuous improvement across engagements
• Approve Statements of Work in partnership with leadership
• Manage resource allocation and ensure projects meet budget and timeline targets

Business Process Automation Practice Manager

Analytics Engineer

• Build and maintain partner data pipelines across APIs, S3, and event flows
• Develop Python and SQL scripts for ingestion, transformation, and delivery
• Own partner integrations including onboarding, monitoring, and issue resolution
• Build dashboards for subscriber metrics, revenue, and partner performance
• Perform analysis on funnel, retention, billing, and attribution
• Troubleshoot data discrepancies and manage incident response
• Define KPIs, data models, and integration specifications
• Support QA and UAT for integration releases
• Work with Product, Engineering, Finance, and external partners

Data Analytics Engineer – Subscription & Partner Integrations

• Lead current state assessment of metadata systems and identify gaps
• Design and build common metamodel and enterprise data model
• Develop and enhance metadata utility platform
• Integrate multiple data formats and systems into unified model
• Create data dictionary and standardized data definitions
• Drive future state architecture and enhancements
• Support testing, validation, and production deployment
• Manage CI/CD setup and system environments
• Conduct knowledge transfer and documentation
• Coordinate with program manager and stakeholders on priorities and delivery

Senior Data Architect – Common Data Model, Metadata Platforms

Program Manager

• Lead complex cross-functional programs from planning through execution and delivery
• Define scope, milestones, deliverables, and success measures with stakeholders
• Build and maintain detailed schedules, work plans, and resource plans
• Track risks, issues, dependencies, and mitigation plans across workstreams
• Provide concise status updates, roadmaps, and presentations to executive leadership
• Drive alignment between program workstreams, business goals, and OKRs
• Monitor KPIs and results to ensure timelines and outcomes are met
• Oversee vendor and partner coordination tied to program objectives
• Support IT transformation initiatives with strong governance and reporting
• Partner with teams on financial planning, forecasting, and program controls
• Drive process improvement, change management, and communications planning

Senior Program Manager – Enterprise IT Transformation

Backend Engineer

• Design and build scalable backend services for metadata ingestion, association, aggregation, normalization, and distribution
• Lead technical design and implementation of new features
• Develop clean, maintainable, and high-quality code
• Partner with engineering leadership and project teams on delivery planning and execution
• Identify system and workflow improvements to increase reliability and scalability
• Support and mentor junior and mid-level engineers
• Contribute to systems that manage large-scale content metadata for downstream platform use