• Assurity is looking for enthusiastic, driven and collaborative people to join our team. We’re a company of vibrant and passionate people who work every day to advance our mission of helping people through difficult times – and who truly want to make a difference. As a Certified B Corporation, we have a verified commitment to our people, community and planet, and we work every day to make the world a better place. Ample opportunities for growth, a thriving culture and coworkers who care as much as you do are just the beginning. Come work with purpose. Learn more: www.assurity.com/careers As a Senior Business Systems Analyst, you are the recognized authority across several business areas and the person our analysts and engineers look to for how analysis gets done. You own the team’s analysis templates, specification standards, and validation checklists; lead the department’s largest and most complex initiatives; shape priorities with business leaders; and mentor analysts and engineers. You direct AI agents on substantial analysis work and set the verification and safety practices that keep the results trustworthy.
ESSENTIAL FUNCTIONS
30% Own business areas, lead discovery, and own the analysis practice, which includes:
- Owning outcomes, priorities, intake, backlog, and business relationships for several business areas and solutions, observing the work with business users, surfacing and sizing the real need, and settling scope and tradeoffs with sponsors in the room rather than after a specification cycle;
- Leading the department’s largest or most complex initiatives, including those that span multiple business areas, analyzing the impact of potential technical difficulties on design, managing scope, cost, and schedule for on-time and on-budget delivery, coordinating solution delivery across teams, and partnering with software engineers on overlapping work, with ownership clarified by your manager;
- Producing and reviewing implementable, AI-ready specifications with decision logic, data definitions, exception handling, and human-in-the-loop review steps that engineers and agents can build from, supported by flow charts, decision tables, data mappings, and acceptance criteria confirmed directly with the users, and keeping them current as implementation questions are resolved with engineers and the business;
- Owning the team’s analysis templates, specification standards, validation checklists, and shared context, such as reusable prompts and instructions, and keeping them current from program evidence; and
- Identifying recurring failure modes in AI-assisted analysis, updating standards to prevent them, and improving controls, guidance, and safe practices for AI use in analysis, including acceptable use, data handling, and human controls, with the responsible policy owners.
20% Build proofs of concept and direct AI agents, which includes:
- Directing AI agents to produce working proofs of concept, such as business rules, workflow steps, portal pages, n8n flows, and letters, or pairing with the architect on code-level proofs of concept, running reaction sessions, and turning feedback into the next iteration within hours or days;
- Generating the business requirements, decision tables, and acceptance criteria from the working solution and keeping them current as it evolves, and delegating substantial analysis work to approved agents, such as stories, data mappings, test plans, and validation queries, with clear intent, business context, constraints, and completion criteria refined as new information emerges;
- Confirming AI-produced analysis against business needs and with business users before it is used;
- Comparing AI, conventional automation, and process change against quality, cost, risk, and user needs, and identifying automation and AI candidates across your business areas, with success measures, and recommending them; and
- Recording material AI contributions and following approved tool and data rules.
15% Test, verify, and shepherd solutions to production, which includes:
- Developing and overseeing test plans, including testing, and managing the testing of, RESTful APIs, Windows services, and database integrations for the most complex work, analyzing test outcomes, resolving differences, ensuring project objectives are met, and reviewing the test results of others as required;
- Leading user acceptance testing for the largest and cross-system initiatives and carrying solutions through dev, test, stage, and production gates with acceptance evidence, evaluation cases, human review steps, and controls verified with the architect, agreeing production ownership and support before release; and
- Establishing verification strategies and review practices for the largest initiatives.
10% Mentor and coach, which includes:
- Mentoring analysts across levels and coaching engineers doing analyst work and business users in the accelerated delivery loop and effective agent delegation;
- Coaching two teammates, or a manager-agreed equivalent, with evidence in their portfolios; and
- Leading solution teams on the largest initiatives, contributing reusable templates, prompts, and context files, and sharing what works as the combined team adopts the accelerated delivery model and agent-directed analysis.
5% Provide system support and troubleshooting, which includes:
- Serving as an escalation point for the business areas’ production issues and supporting systems by reviewing and solving user questions and requests, including on-call rotation.
15% Communicate project status and priorities, and measure value and adoption, which includes:
- Estimating and logging time daily, providing project status information to management and end users, composing professional responses to project inquiries, presenting demonstrations of project functionality, and actively participating in meetings;
- Shaping priorities with business leaders and advising managers and business leaders on scope, sequencing, and tradeoffs; and
- Baselining effort and quality, tracking straight-through rates, review-queue load, adoption, and cost, and reporting results honestly, including what did not work.
5% Innovate and develop professionally, which includes:
- Incorporating new industry developments, including AI capabilities, into future Company systems and keeping abreast of developments that could provide solutions to our business goals; and
- Maintaining skills through ongoing training and study, including AI fluency courses.
The list of essential functions is not exhaustive and may be substituted, as necessary.
HOW WE WANT TO WORK
We build to learn. When a user suggests a change, we put a working version in front of them quickly, often within hours, generate the requirements from what we built, let users react, and then harden the same work through dev, test, stage, and production. People who thrive here:
- Act and decide – Make reversible calls immediately and time-box the rest to hours or days, not weeks. Own the decision and keep stakeholders informed. Slow down deliberately for one-way doors: production data changes, real customer or agent communications, money movement, compliance positions, and security boundaries.
- Show, don’t tell – Bring a working example to the conversation instead of a slide or a specification.
- Hold work loosely – Treat a proof of concept as a question for users. Rework or discard it without attachment when they react.
- Own the outcome – Follow a change through to production and real use, watch monitoring and audit logs, and fix what breaks.
- Leave a trail – Keep generated requirements, decision notes, tests, and agent context files current, along with the specifications and context others rely on, so the next person or agent can pick up the work.
These standards apply to all roles. Associates are expected to demonstrate them within the scope of their position, with the level of independence, decision-making authority, and guidance appropriate for their role.
EXPERIENCE AND SKILL REQUIREMENTS
Required capabilities
- 6+ years of business analyst experience, recognized as a business-area authority, including leading cross-system initiatives.
- Hands-on experience directing AI agents on substantial analysis, documentation, or test-creation work, with sound judgment in validating the output; a practical understanding of prompting, context, retrieval, tool use, evaluations, and AI failure modes; and the ability to independently produce a working proof of concept, agent-directed or low-code, explain its limitations, and design human review and exception handling.
- Experience owning several business areas or the department’s largest initiatives and shaping priorities with business leaders, and writing implementable specifications with decision logic, data definitions, exception handling, and human review steps.
- Experience mentoring analysts across levels and coaching engineers on analysis work, and establishing templates, specification standards, or validation checklists that a team adopted.
- Experience with Agile development and project management, including Scrum; with MS SQL databases (including SQL for data validation) and Mongo; and the ability to read API contracts and JSON.
- Experience testing, and managing the testing of, RESTful APIs, Windows services, and database integrations, using tools such as Postman, Swagger, BrowserStack, Playwright, or other automated test scripting, and creating and maintaining test suites.
- Experience creating project charters, work summaries, and workflows in Lucid or a similar tool.
- Strong analytical, troubleshooting, planning, facilitation, stakeholder, and decision-making skills, including making and defending decisions with incomplete information, professional written and verbal communication, and organizational skills to manage multiple tasks within the constraints of timelines and budgets, with business acumen.
- Ability to thrive in a fast-paced remote team environment, to learn rapidly and master diverse technologies and techniques, and to learn a business domain quickly from its data, its code, and its users.
- Talent required in values, work intensity, achiever, positivity, resourcefulness, command, relationship-extension, and exactness.
Preferred experience
- Knowledge of Claude, Claude Code, Microsoft CoPilot, or similar agentic tools; n8n; Git and GitHub; Azure DevOps or Jira; ability to read C#, Python or TypeScript.
- Experience identifying automation and AI opportunities and defining success measures; decision tables and business rules, workflow and state-machine design, and human-in-the-loop review design.
- Insurance or financial services experience, such as new business, underwriting, claims, or policy administration.
AI FLUENCY
Directing AI agents is the default way you produce work on this team. You choose another approach when quality, security, or the platform calls for it, and can explain why. You own the correctness, security, and quality of everything you deliver, however it was produced.
- Delegation – Routinely directs agents on substantial analysis work, such as requirements, decision tables, user stories, data mappings, test plans, and validation queries, where they suit the task. Choose a sensible division of work between you and the agent, explain significant exceptions, and recover when an agent becomes unproductive.
- Description – Give agents clear intent, business context, constraints, and completion criteria, and improve them as new information emerges. Clarifying questions, prompt revisions, and discovering a genuine requirement gap are normal parts of good work. Establish AI-ready specifications, templates, or context practices that demonstrably improve work across the team, including decision logic, data definitions, exception handling, and human-in-the-loop steps, and set standards for requirements generated from working solutions, including guardrails.
- Discernment – Confirm AI-produced analysis against business needs and with business users before it is used. Explain the result and its limit, redirect or stop ineffective work, and own and learn from defects. Establish verification strategies and review practices, design evaluations and success measures for AI-enabled workflows, identify recurring failure modes, and improve the team’s quality of judgment.
- Diligence – Follow approved tool and data rules independently, protect sensitive evidence, record material AI contributions, and raise control gaps promptly. Improve controls, guidance, and safe practices, including AI acceptable-use guidance, for others with the responsible policy owners and build them into how the team works.
- Leverage – Apply repeatable AI workflows to recurring analysis and testing work and show a credible benefit in delivery time, clarity, coverage, quality, or reduced effort. Count verification and rework honestly and explain limitations.
EDUCATION AND CERTIFICATION REQUIREMENTS
Bachelor’s degree in a related field or equivalent experience. Relevant technical, analysis, cloud, insurance, or leadership certifications are beneficial; demonstrated capability remains central.
PHYSICAL AND WORK SCHEDULE REQUIREMENTS
This position is remote, with occasional on-site attendance. Travel arrangements and team collaboration hours are communicated for the specific opening. Consistent and reliable attendance is an essential function. Work may exceed 40 hours a week.
- On-call rotation – Participates in a rotating on-call schedule after training, including nights and weekends. While on call, remains reachable and responds promptly to production alerts within defined response times and escalation paths.
- Contain first – While on call, is empowered to take immediate containing actions, such as rolling back a release, pausing outbound communications, parking workflows, or disabling a feature. Fixes forward during business hours unless impact requires otherwise, and records a brief incident note.
- Planned off-hours work – Occasional scheduled evening or weekend work for production deploys, cutovers, data migrations, and go-lives, with advance notice.
Note: We are not currently considering applicants in CA, CO, CT, DC, HI, IL, MA, MD, MN, NV, NJ, NY, RI, VT, WA, for this position.