Job Openings Senior Level — Enterprise/Solution Architect (Life Sciences)

About the job Senior Level — Enterprise/Solution Architect (Life Sciences)

Senior Level — Enterprise/Solution Architect (Life Sciences)

75hr W2 or $85hr c2c/1099 – Self Corp

Location: Foster City (on-site / hybrid)
12 plus months(W2)
Level: Manager/ Individual Contributor
Reporting to: Head of Enterprise Architecture

Ok with H1

Should have background related to Finance and AI

Overall 15+ years required


Role summary

We are seeking a senior-level Enterprise / Solution Architect to drive enterprise and solution architecture initiatives with a strong focus on Finance domain capabilities within a Life Sciences organization. This role will be responsible for translating business and finance strategy into scalable, secure, and compliant target-state architectures, while enabling modernization through AI-driven solutions, including agentic and autonomous architectures.

The role requires deep expertise in Finance systems and controls, experience operating in regulated environments, and hands-on architecture leadership across cloud, data, integration, security, and AI platforms.

Key responsibilities

  • Define, evolve, and socialize enterprise and solution architecture strategies and roadmaps with primary ownership of the Finance domain (Record to Report, Order to Cash, Procure to Pay, FP&A, Treasury).
  • Ensure architecture designs meet financial compliance and control requirements, including Sarbanes-Oxley (SOX) and broader audit and regulatory standards.
  • Lead solution and architecture reviews; ensure adherence to architectural principles, security, scalability, and compliance expectations.
  • Design target-state application, data, and integration architectures, leveraging APIs, event-driven patterns, and canonical data models.
  • Provide architectural guidance for AI-enabled finance solutions, including:
  • Scalable AI/ML platform architectures
  • Agentic AI solutions and multi-agent orchestration
  • Model Context Protocol (MCP) and Agent-to-Agent (A2A) interaction patterns
  • Partner closely with Finance, IT, Security, and Compliance stakeholders to align architecture decisions with business outcomes.
  • Establish and operate architecture governance processes including intake, review, approval, and compliance tracking.
  • Provide architectural oversight for major finance and enterprise programs, modernization initiatives, and cloud transformations.

Deliverables

  • Documented enterprise and finance-domain architecture vision with a 12–24 month roadmap.
  • Architecture decision records (ADRs) and reference designs for:
  • Finance platforms and integrations
  • AI-enabled finance use cases
  • Cloud landing zones, data platforms, and identity & access management
  • Operationalized architecture governance with clear compliance checkpoints.
  • Prioritized view of technical debt and modernization opportunities.

Required qualifications

  • 15+ years of overall technology experience with 5+ years in enterprise or solution architecture roles.
  • Strong Finance domain architecture expertise, including systems, data, controls, and compliance.
  • Practical experience working with Sarbanes-Oxley (SOX) controls and audited environments.
  • Strong architecture skills across:
  • Cloud platforms (AWS / Azure / GCP)
  • Microservices, APIs, and event-driven architectures
  • Data platforms (Lakehouse, warehouse, analytics)
  • Security, IAM, and enterprise integration (ESB, iPaaS)
  • Solid experience with architecture frameworks and governance (TOGAF, ArchiMate, or equivalent).
  • Excellent stakeholder management skills with the ability to communicate complex concepts to both technical and non-technical audiences.

Preferred skills & certifications

  • Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent experience.
  • Certifications such as TOGAF, AWS/Azure/GCP Professional, CISSP, or PMP.
  • Experience in digital transformation initiatives within Life Sciences, Pharma, or regulated industries.
  • Prior exposure to AI/ML platforms in regulated, enterprise-grade environments.