AI Collaborator/Developer

SUMMARY

Bring in an AI-first practitioner who compresses delivery timelines by orchestrating Claude (and other LLMs) across the full development lifecycle, while maintaining the architectural and product judgment that makes the output durable. This person is a force‑multiplier: one of them replaces a small team for the right kind of work and produces artifacts that survive enterprise review.

PRIMARY DUTIES

How This Person Operates Directs and guides AI across planning, solution design, development, documentation, and UAT – treating the AI as a capable but literal collaborator that needs clear acceptance criteria to perform well. Defines what "good" looks like up front (acceptance criteria, conformance checks, architectural fit) and validates AI output against that standard rather than rubber‑stamping it. Owns end‑to‑end delivery from ideation through production and iteration; acts as product thinker, architect, and delivery lead — not just an executor. Practices context engineering: knows what reference material (code collections, schemas, utility libraries, prior decisions, SOPs) to feed the model, how to scope work so AI has enough context to succeed but not so much it drifts, and how to manage long‑running sessions and context windows. Builds living documentation as a deliverable, not an afterthought – Mermaid/BPMN diagrams, structured SOPs, and conformance criteria that make AI output checkable against intent over time. Breaks work into well‑defined, digestible units with clear acceptance criteria. Validates requirements with business stakeholders to surface and eliminate legacy holdovers rather than encoding them into new systems.

COMPETENCY

Ideal Background Hands‑on developer history combined with architectural and product ownership; can drop into code to debug, spike, or validate AI output, but doesn't default to hand‑coding as the primary delivery mode. Experience owning product state and requirements, not just implementing tickets. Comfortable questioning legacy patterns, improving designs rather than replicating them, and pushing back constructively on stakeholder requests that don't hold up. Has worked inside enterprise environments with real constraints (security, change management, internal source control, data governance) – this is not a greenfield startup role. Uses LLMs to perform the majority of development and maintenance work; spends own time on planning, orchestration, validation, and outcome alignment. Knows how to be prescriptive with AI – preventing it from doing the bare minimum, catching when it confabulates, and structuring prompts and context so output is fit‑for‑purpose the first time rather than the third. Exercises judgment about when not to use AI – recognizes when a 10‑minute hand edit beats a 40‑minute prompt‑and‑validate cycle. Avoids AI ceremony for its own sake. Familiar with patterns like CLAUDE.md / project context files, MCP servers and tool integration, structured outputs, and managing parallel or long‑running agent sessions. Claude Certified Architect (CCA) credential is a plus but not required; demonstrated production work matters more than the badge. Required: GitHub (comfortable with enterprise/internal GitHub instances, not just public repos); strong source control discipline. Strongly preferred: Claude (Desktop, Code, or both); experience configuring MCP servers and skills for enterprise contexts. Plus: SQL Server / data warehousing background; XML/XQuery exposure or willingness to ramp on MarkLogic; insurance or other regulated‑industry experience. Comfort with mainstream stack tools is assumed (CI/CD, basic cloud literacy, common IDEs).

EXPERIENCE

Overall experience: 8–15+ years AI‑first / LLM workflow experience: 1–3+ years (or equivalent demonstrated production use)

PHYSICAL DEMANDS

Regular use of hands and fingers to operate a computer keyboard, mouse, and other office equipment. Regular, repetitive movements such as typing, mouse movements, and scrolling; ability to hear and understand spoken communications, both in person and via remote communication tools (e.g., phone, video conferencing). Ability to see and read computer screens and printed documents, as well as adjust focus; includes prolonged periods of looking at a computer screen.

WORK ENVIRONMENT

Onsite preferred but will consider fully remote candidates.

EXPECTED HOURS OF WORK

Monday–Friday, 40 hours per week, with flexibility as required to meet project deadlines or customer needs.

TRAVEL

NA Hybrid Role Clarification ***This is a hybrid role and the candidate is expected to work in the office and/or job site 3 days a week. #J-18808-Ljbffr Dancrai Pty