AI Collaborator​/Developer

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At New Era, you'll join a team-oriented culture that prioritizes your personal and professional development. Work alongside industry-certified experts, access continuous training, and enjoy competitive benefits. Guided by our core attributes — putting people first, embracing continuous learning, and thriving through collaboration and inclusion — we nurture our people to deliver exceptional customer service.

If you want to make an impact in a supportive, growth-oriented environment, New Era is the place for you. Apply today and help us shape the future of work—together

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 force-multiplier-shaped: one of them replaces a small team for the right kind of work and produces artifacts that survive enterprise review.

• 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‑staking 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

• 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 their 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:
  
  Git Hub (comfortable with enterprise/internal Git Hub instances, not just…