Staff II Software Engineer

Job Summary

Make Your Mark: 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.

You'll Get To:

• 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.
• 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.

What You'll Bring:

• 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.

We're Even More Excited If You Have:

• Experience with Google Vertex AI Agent Builder or similar managed agent platforms.
• Hands-on experience with Temporal for durable workflow orchestration in FinTech or regulated environments.
• Deep GCP expertise: Vertex AI, GKE, Cloud Workflows, Pub/Sub, BigQuery deployed in production.
• Familiarity with SOX, GDPR, or financial compliance audit requirements and how they constrain system design.
• Contributions to open-source AI/agent frameworks (LangChain, Temporal, etc.).
• Experience with multi-modal models (vision, audio, code generation).
• Published research, conference talks, or technical blog posts on agentic AI or AI governance topics.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.