Senior Software Engineer - Applied AI

Opplane provides data-focused solutions for digital transformation in financial services, telecommunications, and reg-tech. The Senior Software Engineer - Applied AI will design experiments, build analytical and evaluation pipelines for AI capabilities, and apply findings across the software delivery lifecycle. The role also involves partnering with platform teams, supporting constrained engineering teams, and communicating evidence-based recommendations to leadership and finance.

Responsibilities:

• Design and run experiments. Model tier routing, MCP coverage, permission configuration, repository context quality, budget headroom — randomized across teams and reported with their limits stated. These are the cleanly causal questions available once a tool is deployed, and where the returns are
• Own the analytical layer of the measurement program: work classification over model traffic, evaluation design, longitudinal within-unit analysis, and the staggered-adoption estimates that connect delivery outcomes to adoption timing
• Build and validate LLM-as-judge and classification pipelines — sampling strategy, hand-labeled ground truth, precision and recall measured and published, and revalidation whenever the taxonomy or the model changes
• Extend AI beyond code authoring into the stages that constrain delivery: test authoring and maintenance, environment and data setup, migration and modernization, code review assistance, security remediation, and evidence assembly for certification
• Work directly with the constrained teams. Where validation or certification is the bottleneck, coding assistance produces little regardless of how well it works — find where the constraint actually sits and aim the capability at it
• Build evaluations for internal AI capabilities: golden sets, regression suites, groundedness and answer-quality scoring, and the cost and latency telemetry beside them
• Turn findings into practice. Identify what the most effective practitioners do differently, document it, and teach it — publishing practices rather than rankings
• Partner with the platform team on Claude Code configuration, MCP servers, gateway telemetry, and the model registry, so what you learn becomes the default rather than folklore
• Report to engineering leadership and finance: what is working, what is not, where delivery is actually constrained, and what each claim does and does not establish