Lead Software Engineer

We are the leading provider of professional services to the middle market globally, our purpose is to instill confidence in a world of change, empowering our clients and people to realize their full potential. Our exceptional people are the key to our unrivaled, culture and talent experience and our ability to be compelling to our clients. You’ll find an environment that inspires and empowers you to thrive both personally and professionally.

There’s no one like you and that’s why there’s nowhere like RSM.

• 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.

• 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.

• Deep expertise in modern programming languages and frameworks such as Java, C#, Python, JavaScript/Type Script, and Rust.
• Proficiency with databases (SQL, No
  
  SQL) and API design/integration.
• Experience with cloud-native applications on AWS, or GCP.
• Familiarity with Dev Ops practices (CI/CD, containerization, automated testing).
• Solid grasp of modern architecture patterns, including microservices and event-driven systems.
• Practical experience in streaming/event platforms like Kafka, Pub/Sub, Kinesis
• Practical experience deploying and serving models with vLLM, Ollama, or LM Studio.
• Applied experience with RAG and GraphRAG pipelines, including embedding models, chunking and retrieval strategies, and vector databases such as Pinecone, Weaviate, Milvus, Qdrant, Chroma, and pgvector.
• Familiarity with supporting orchestration and tooling such as Lang Chain, Llama Index, and knowledge-graph stores (e.g., Neo4j) for GraphRAG workloads.
• Excellent leadership, communication, and stakeholder management skills.
• Strong…