We are seeking a hands-on technical consultant to help a software engineering team use AI effectively in its day-to-day work. The role combines software development experience, practical coaching, and the ability to analyze how work moves through an engineering organization. You will work directly with the engagement lead, developers, quality assurance staff, and release owners at an industrial technology company. The focus is one engineering team working within a selected release. The initial assignment is approximately three weeks of discovery, with an estimated commitment of 15–20 hours per week. There is potential to extend into implementation of the adoption plan and developer coaching, subject to project approval.
What you will do: During discovery:
- Interview engineers and review working examples to understand the development process, current AI use, and coaching needs.
- Map key activities and handoffs across requirements, development, testing, review, and release documentation.
- Identify practical opportunities for AI assistance, distinguishing them from constraints caused by equipment availability, workload, or approvals.
- Assess the team’s readiness, access requirements, and available assignments. Develop a focused plan for setup, coaching, and continued use.
- Define practical measures of effort, quality, rework, and adoption. Support the technical assessment of one potential agent workflow.
- If the engagement extends into adoption delivery:
- Coach developers on real assignments using approved AI tools, including code exploration, change preparation, test development, and documentation.
- Help engineers review, test, and correct AI-generated outputs and recognize when to change approach.
- Configure approved capabilities and create reusable instructions, examples, and review checklists.
- Support an internal champion and help the team become confident using the methods independently.
- Document results, lessons, and recommendations in clear client-facing materials.
- What you bring
- Recent hands-on experience in software development, QA automation, developer productivity, or a comparable technical role.
- Practical experience using AI coding assistants on existing codebases. Claude Code experience is valuable; strong experience with comparable tools is also relevant.
- Demonstrated ability to teach technical colleagues through code walkthroughs, pairing, training, or mentoring.
- Sound judgment about code quaality, testing, source context, and the limitations of AI-generated work.
- Strong interviewing, process-analysis, and writing skills.
- Ability to work independently, build credibility with engineers, and turn observations into practical recommendations.
- Experience with industrial software, complex established codebases, or hardware-dependent testing is helpful.
What success looks like:
Discovery produces a clear, validated adoption plan grounded in the team’s actual work. During any subsequent delivery phase, engineers learn repeatable methods, produce reviewed outputs, and demonstrate that they can continue using those methods independently. To express interest Please share your résumé or LinkedIn profile, earliest start date, weekly availability, and hourly rate. Include a brief example of how you have helped developers use AI effectively and a relevant work sample you are permitted to share.
