Lead Software Engineer - AI, Cloud & Systems Architecture

RSM US LLP

Los Angeles (CA)

Hybrid

USD 127,000 - 224,000

Full time

7 days ago

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Benefits offered by this job

Hybrid work model

Discretionary bonus

Job summary

RSM US LLP in Los Angeles area is seeking a Lead Software Engineer to design and deliver cloud-native platforms that support complex workflows, data-intensive apps, and AI-enabled capabilities. You will lead architecture across distributed systems, APIs, data pipelines, and governance, while mentoring teams to raise the bar in engineering practices and delivery discipline.

Hybrid role with emphasis on secure, scalable solutions; candidates with strong leadership and experience in regulated

Qualifications

5-7 years of experience in software engineering, with at least 2 years in a leadership or architectural capacity.
Experience managing teams and delivering solutions in complex or regulated environments.

Responsibilities

Lead the design, development, and delivery of secure, scalable, cloud-native software platforms that support complex business workflows, data-intensive applications, and AI-enabled capabilities.
Provide technical leadership across architecture, engineering design, code quality, testing strategy, deployment practices, and operational readiness for high-impact solutions.
Design and guide implementation of distributed systems, APIs, microservices, event-driven workflows, data pipelines, and integration patterns that are reliable, observable, and maintainable.
Drive architecture decisions that separate shared platform services, application-specific logic, calculation engines, and user experience layers to reduce duplication and improve system consistency.
Partner with product owners, architects, data teams, AI/ML engineers, security, and business stakeholders to translate ambiguous requirements into practical technical designs and delivery plans.
Build and evolve systems that preserve provenance, lineage, auditability, version history, and traceability from source data through transformed, computed, and user-facing outputs.
Develop and support configuration-driven platforms where rules, mappings, thresholds, policies, and business logic can be governed, versioned, approved, and executed without unnecessary code changes.
Guide engineering teams in implementing deterministic execution patterns, including dependency graphs, workflow orchestration, idempotency, replayable processing, caching, failure isolation, and recomputation strategies.
Support AI-enabled solution design, including RAG, GraphRAG, vector retrieval, knowledge graphs, model-serving patterns, model evaluation, and guardrails that ensure outputs are explainable, grounded, and reviewable.
Review and validate technical deliverables, architecture artifacts, pull requests, data models, integration designs, and operational controls to ensure quality, security, scalability, and compliance with engineering standards.
Coach and mentor engineers by raising the technical bar, promoting first-principles problem solving, encouraging thoughtful tradeoffs, and strengthening team capability in modern software engineering practices.
Continuously improve engineering practices, CI/CD pipelines, automation, observability, testing coverage, documentation, and incident response processes.
Serve as an escalation point for complex technical decisions, production issues, architectural tradeoffs, and cross-functional dependencies.
Contribute to technology strategy, platform modernization, departmental planning, and cross-functional initiatives that support reusable, governed, and extensible enterprise systems.