Lead Software Engineer, Reporting

Envestnet

Location: ALL USA
Workplace: Remote
Employment: Full Time
Salary: USD 152,300–190,400/yr

Posted 2mo ago

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Responsibilities

Architect and design systems, services, or platforms with broad impact.
Lead technical decision-making for major features or initiatives.
Drive cross-team collaboration and align technical solutions with business goals.
Establish and enforce best practices in architecture, coding, and deployment.
Anticipate technical risks and proactively implement mitigation strategies.
Lead incident response and root cause analysis for critical issues.
Influence roadmap planning through technical insight and feasibility analysis.
Specialize in AI/ML integration, LLM-based features, and AI platform engineering.
Actively utilize agentic coding tools (e.g., Claude Code, GitHub Copilot) throughout the SDLC.
Translate complex business requirements into robust, maintainable technical solutions.
Partner with cross-functional teams, including QA and business stakeholders.
Perform code reviews and drive adherence to engineering best practices.
Deliver on individual and team commitments.
Mentor and develop engineers.
Provide ongoing support, enhancement, and maintenance of Python-based AI/ML applications.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field required; master’s degree preferred.
8+ years of software engineering experience, including technical leadership for major features, systems, services, or platforms with broad impact.
Strong technical background with .NET, xUnit, Reqnroll, RESTful APIs, and API management solutions such as Apigee.
Experience with PostgreSQL, SQL Server, Redis, and ElastiCache.
Experience with AWS services including EC2, S3, ELB, ASG, API Gateway, Lambda, RDS, EKS, CloudWatch, SQS.
Experience with Kubernetes, Docker, Kafka, CloudFormation, CDK, Terraform, DevOps practices, automation, agile delivery, Scrum, and test-driven development.
2+ years designing, delivering, or integrating production-grade AI/ML systems, LLM-based applications, AI platform capabilities, and agentic workflows.
Experience with Python-based AI/ML application support, enhancement, maintenance, reliability, scalability, and production readiness.
Strong knowledge of AI cost control, evaluation, governance, LLM integration patterns, stateful agents, memory patterns, and practical AI use case delivery.
Experience with event-driven architectures, Kafka or asynchronous messaging, cloud infrastructure such as AWS, GCP, or Azure, and observability practices.
Demonstrated ability to lead architectural decisions, define technical standards, conduct code reviews, and communicate trade-offs.
Experience in fintech, reporting, real-time financial platforms, regulated production environments, or other domains requiring strong data consistency, idempotency, fault tolerance, and scalability.
Hands-on experience using agentic coding tools such as Claude Code or GitHub Copilot to accelerate feature delivery, code review, testing, and SDLC execution.

Skills

Java
Python
Spring
SQL
NoSQL
RESTful APIs
AWS
EC2
S3
ELB
ASG
API Gateway
Lambda
RDS
EKS
CloudWatch
SQS
Kubernetes
Docker
Kafka
CloudFormation
CDK
Terraform
DevOps
Agile
Scrum
Test-driven development
AI/ML
LLM
Agentic coding tools
Claude Code
GitHub Copilot
.NET
xUnit
Reqnroll
Apigee
PostgreSQL
SQL Server
Redis
ElastiCache
GCP
Azure
Event-driven architectures
Asynchronous messaging

Responsibilities

Requirements

Skills

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