JobHabor

Senior Software Engineer

Envestnet

Location
United States
Workplace
Remote
Employment
Full Time
Salary
USD 124,000–155,000/yr
Apply on the employer’s site

Posted 2mo ago

The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.

Responsibilities

  • Design, develop, and maintain .NET services
  • Contribute to analytics platforms
  • Implement features using modern architecture patterns
  • Build and integrate AI enabled capabilities
  • Participate in building multi-step AI workflows
  • Contribute to agent memory implementations
  • Ensure code meets standards for performance, reliability, security, and observability
  • Collaborate closely with Product Managers, QA, data teams, and external partners
  • Participate in code reviews, design discussions, and technical refinements
  • Support test automation, CI/CD pipelines, and production readiness practices
  • Adherence to and application of Envestnet legal, compliance, risk, business continuity and administrative policy

Requirements

  • 6–10 years of backend engineering experience
  • Strong expertise in .NET / C#
  • Experience building distributed systems
  • Exposure to analytics platforms, reporting systems, or data intensive services
  • Hands-on experience with AI / ML or Generative AI
  • At least 1+ year in production or advanced POC environments
  • Understanding of data consistency, fault tolerance, scalability, and performance tuning
  • Ability to take ownership of features and deliver high-quality solutions in an agile team

Preferred

  • Exposure to stateful AI agents, workflow orchestration, or AI pipeline components
  • Strong collaboration skills and experience working with cross functional stakeholders
  • Experience in fintech or regulated domains
  • Familiarity with RAG architectures, vector databases, or prompt orchestration
  • Experience working in cloud and Kubernetes based environments

Skills

  • .NET
  • C#
  • SQL
  • Distributed Systems
  • Analytics Platforms
  • Cloud
  • Kubernetes
  • Generative AI
  • Agentic AI
  • Lang Graph
  • Security
  • Observability
  • RAG architectures
  • Vector databases
  • Prompt orchestration

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