• You will be the chief system designer, provide mentorship to other devs, and be the bridge between product requirements and the business team.

• Write well designed, testable, efficient code by using best software development practices. • Contribute in all phases of the development lifecycle. • Support continuous improvement by investigating alternatives and technologies and presenting these for architectural review. • Proposes initial technical implementation which supports architectural changes that solve scaling and performance problems. • Work with version control using GitHub, conflict resolution, and automation of continuous integration processes. • Create and maintain software documentation.

• Full-stack software development • Deployments & support of existing apps • Client meetings & project planning • Architecture design • Mentorship of junior team members

• Own the reference architecture for LLM/AI features (service boundaries, APIs, data contracts, trust boundaries, deployment patterns) • Convert prototypes into production-ready services with clear interfaces, type/schema discipline, and controlled dependencies • Define versioning strategy for prompts, tools, policies, and model endpoints (including rollbacks) • Design and implement LLM pipelines for natural language → structured queries for database engines with guardrails • Implement schema-first output (e.g., Pydantic models / JSON schema) and robust parsing/validation • Own non-functional requirements: latency budgets, throughput, resilience, and cost control • Build observability: structured logs, traces, metrics, and error taxonomies that make failures actionable • Translate requirements from client stakeholders and internal security / engineering teams into robust AI-enabled solutions and data integrations • Act as the technical lead for Applied AI delivery: raise engineering bar, mentor DS/engineers, and drive code quality • Document solutions and participate in knowledge transfer with internal and partner teams.