Staff II Software Engineer
Overview
We are looking for an accomplished, deeply hands-on Senior Staff Engineer with 15+ years of software engineering experience and a focused track record in Agentic AI,Generative AI systems and Software/Data engineering. This is a senior individual contributor role that combines architectural leadership with direct execution - you will drive the design and delivery while simultaneously guiding and unblocking a team of Staff Engineers and Technical Leads.
The ideal candidate has independently driven 3-4 end-to-end AI implementations - from requirements gathering and solution design through to production deployment - and is equally comfortable whiteboarding complex multi-agent architectures and writing production-grade Python. You bring the experience to set the technical direction, the judgment to make critical architecture decisions, and the hands-on depth to get into the code when the team needs unblocking.
This role demands breadth and depth across the stack: you will architect scalable AI systems, build and orchestrate intelligent agents, embed robust agent governance frameworks, and establish the engineering standards that make those agents enterprise-ready for a secure and compliant financial platform.
Responsibilities
- Own 3-4 complete AI delivery cycles: discovery, requirements, solution design, build, test, and production deployment on GCP or any cloud.
- Translate ambiguous business problems into concrete solutions with clear success metrics.
- Define and manage delivery milestones across cross-functional stakeholders including Finance, Compliance, and Platform Engineering.
- Lead architecture decision records (ADRs), design reviews, code reviews, and production readiness assessments.
- Set quality bars for the team: performance benchmarks, eval thresholds, observability standards, and security posture.
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This role carries explicit responsibility for the technical growth and day-to-day unblocking of Staff Engineers and Technical Leads working across the Agentic AI platform.
- Architecture Decomposition: Break down the platform into clear workstreams and assign ownership to Staff Engineers with explicit API contracts and interface definitions.
- Hands-on Unblocking: When Staff Engineers or Tech Leads are stuck on system design decisions, integration challenges, or production issues - step in directly with code, design sketches, or paired debugging sessions. This is not a review-only role.
- Design Guidance: Review component-level designs proposed by Staff Engineers, identify gaps in governance, observability, or compliance thinking, and guide them to better solutions without simply overriding.
- Standards Setting: Define and document engineering standards for the agentic AI domain: agent identity patterns, audit trail requirements, HITL design principles, Kafka topic design, and eval harness setup.
- Mentorship: Run architecture working sessions, design clinics, and 1:1 coaching with Staff Engineers and Technical Leads to build their depth in agent governance and FinTech compliance patterns.
- Cross-Team Influence: Align architecture decisions across Engineering, Security, Compliance, and Data Platform teams. Represent the AI Platform in cross-functional technical forums.
- Architect the Agentic AI System: agent registry, policy engine, metrics ingestion pipeline, anomaly detection, and HITL orchestration.
- Design multi-agent pipelines with clear trust tier boundaries (T0-T3), separation of concerns, fault isolation, and full observability.
- Define data flows, integration patterns (REST, gRPC, SSE, event-driven), and storage strategies for AI workloads in a multi-tenant FinTech environment.
- Design the durable DAG execution, pause/resume for long-running financial close workflows, event-sourced audit trail, and SLA-tracked HITL approval gates.
- Present technical proposals, architecture trade-offs, and risk assessments to senior leadership and key stakeholders.
- Design, build, and deploy intelligent agents for complex, multi-step financial reasoning tasks
- Implement agent orchestration using LangGraph , Temporal, Google Workflows, or equivalent - with documented rationale.
- Deploy agents on GCP (Vertex AI Agent Builder, Cloud Run, GKE) or AWS / Azure equivalents; establish K8s namespace isolation for T1 certified partner agents.
- Implement MCP (Model Context Protocol) server and client patterns for external agent integration (T2/T3 trust tiers via SSE/HTTPS).
- Implement ReAct, Plan-and-Execute, and other advanced prompting and reasoning strategies suited to accounting domain tasks.
- Design and implement RAG pipelines with vector stores (Pinecone, Weaviate, pgvector) for domain-specific financial document retrieval.
- Fine-tune, prompt-engineer, and evaluate foundation models (Gemini, GPT-4, Claude) for accounting-domain tasks including close commentary generation and variance explanation.
- Optimise inference costs through caching, batching, model routing, and quantisation strategies; maintain token cost visibility in Control Tower.
- Build evaluation harnesses to benchmark model quality, factuality, and safety at scale - integrated into the T1 agent certification pipeline.
Qualifications
- 15+ years of software engineering experience with broad distributed systems depth across enterprise platforms.
- 3-4 years of focused hands-on experience in Agentic AI and/or Generative AI systems - building, deploying, and operating multi-agent platforms at production scale.
- Demonstrated delivery of 3-4 full E2E AI projects from requirements through production deployment.
- Proven experience guiding and unblocking Staff Engineers and Technical Leads - setting architecture direction, reviewing designs, and stepping in hands-on when needed.
- Minimum 90% hands-on design and implementation - this is a Senior Staff Individual Contributor role with technical leadership responsibilities, not a management role.
- Experience architecting and deploying complex, production-grade systems at scale in regulated industries (FinTech, Financial Services, Healthcare) is strongly preferred.
