Software Engineer II

Assurity•Lincoln, NE

19h•Remote

About The Position

Assurity is hiring a Software Engineer II to deliver software and AI- and automation-enabled solutions, taking work from proof of concept through testing, production release, and real-world operation. The role owns stories and features end to end, often working directly with business users to define requirements and acceptance criteria. The engineer directs AI agents on substantial development and testing tasks, verifies their output, and writes code directly when the task or quality requires it. They are accountable for the quality, security, and correctness of all deliverables, regardless of how they were produced. The role involves building components, integrations, business logic, services, consoles, LLM-integrated workflows, and n8n flows; integrating model APIs, retrieval, tool calling, and MCP; and working with back-end services and databases. The engineer writes and maintains tests, evaluations, documentation, logging, error handling, and rollback capabilities, and promotes changes through CI/CD environments while monitoring production systems. Responsibilities also include participating in a rotating on-call schedule, responding to incidents and user requests, applying human-review and access-control safeguards, collaborating with analysts and senior engineers, and maintaining technical and AI fluency. This is a remote position with occasional on-site attendance. Team collaboration hours and travel arrangements are communicated for the specific opening. The role may exceed 40 hours per week and includes rotating on-call coverage after training, including nights and weekends, as well as occasional scheduled evening or weekend work for deployments and other production activities. Applicants in certain listed states and cities are not being considered for this opening.

Requirements

At least two years of professional software development experience.
A portfolio of work shipped iteratively with AI agents and sound judgment in verifying agent output; the interview includes a live build exercise.
Hands-on experience with model API integration, retrieval, tool calling, and evaluation.
Experience with relational databases such as PostgreSQL or SQL Server, object-oriented programming, and web application development.
Strong Python or TypeScript skills and experience building and consuming REST APIs.
Experience building interfaces with modern HTML/CSS and building functional solutions using more than one of Vue, Angular, JavaScript, .NET MVC, Entity Framework, or REST.
Ability to design and implement unit and integration tests and debug with modern IDEs, preferably Visual Studio.
Experience with modern source control and CI/CD release pipelines, preferably Azure DevOps and Git; containers; Agile processes; and modern data formats, preferably JSON and XML.
Experience writing user stories and acceptance criteria and working directly with business users to confirm completed work.
Strong problem diagnosis, troubleshooting, creative problem-solving, and professional written and verbal communication skills.
Strong organizational skills to manage multiple tasks within timeline and budget constraints, along with business acumen.
Ability to thrive in a fast-paced remote team environment and rapidly learn diverse technologies and techniques.
Talent in values, work intensity, achiever, positivity, resourcefulness, command, relationship-extension, and exactness.
Bachelor’s degree in a related field or equivalent experience.
Ability to follow approved AI-tool, data, and access rules; protect secrets and sensitive data; document material AI contributions; verify AI-generated work; and take responsibility for defects and control gaps.
Ability to participate in a rotating on-call schedule after training, including nights and weekends, and respond promptly within defined response times and escalation paths.
Reliable attendance and ability to work more than 40 hours per week when required.

Nice To Haves

Claude Code or similar agentic tools.
Python/FastAPI, TypeScript, Next.js, C#, React, n8n, or MCP experience.
Azure DevOps or Jira, GitHub Actions, Podman or Docker, or Azure experience.
PostgreSQL and SQL Server, Kafka or Redpanda event streaming, Neo4j, Grafana and Prometheus, or LDAP/Active Directory experience.
Insurance or financial services systems and enterprise integration experience.
Relevant technical, analysis, cloud, insurance, or leadership certifications.

Responsibilities

Direct AI agents to build and harden features, fixes, and proofs of concept in the real codebase, from working versions presented to users through production; write code directly when appropriate.
Design and build software components, integrations, and business logic, and translate functional specifications into code solutions.
Implement retrieval, tool calling, and MCP integrations with model APIs such as Anthropic and Azure OpenAI.
Integrate data from back-end services and databases, and maintain, expand, and scale enterprise software.
Write unit and integration tests and evaluations; verify agent-produced changes through testing, debugging, and review appropriate to their risk before release.
Build logging, error handling, and rollback into solutions.
Create and maintain software documentation, repository instructions, reusable prompts, and validation methods.
Promote changes through CI/CD release pipelines across development, test, stage, and production; monitor shipped work and follow it through to real use.
Participate in on-call shifts, resolve production alerts and incidents, and handle user questions and requests for owned systems promptly.
Write stories and acceptance criteria, confirm them directly with business users, and validate completed work through acceptance testing and rollout.
Apply human review, access control, audit, communication egress, and simulation patterns.
Coordinate with business systems analysts and senior engineers, pair with analysts on proofs of concept in user sessions, and review peers’ changes.
Estimate and log time daily, provide project status information to management and end users, and demonstrate project functionality.
Share proven agent-directed delivery patterns across the team.
Maintain skills through ongoing training and study, including AI fluency courses, and evaluate emerging trends and AI capabilities for fit.
Follow work through to production and real use, monitor systems and audit logs, and address issues that arise.
While on call, take immediate containment actions when needed, such as rolling back releases, pausing outbound communications, parking workflows, or disabling features; document incidents.
Perform occasional scheduled off-hours production deployments, cutovers, data migrations, and go-lives with advance notice.