Staff Software Engineer - Platform and Cloud Services

Agiloft

21d

About The Position

This is a foundational engineering role. You will own a critical domain of the platform on which Agiloft's CLM product is built as one of a small team of staff engineers who each own a core part of the platform and shape its direction together. This is a backend- and distributed-systems–weighted position with deep ownership of your domain and end-to-end accountability for its design, scalability, reliability, and security as the product and customer base grow. You will work across the organization with engineering leaders, senior engineers, product leaders, and partner teams to understand where the product is going, translate business and product goals into durable platform architectures, and align diverse stakeholders on the technical direction. This means, you will set architectural direction alongside a peer group of staff engineers of your caliber. This is a hands-on leadership role that combines deep backend and cloud expertise with the influence to drive architecture across functional boundaries.

Requirements

Bachelor's and/or master's degree in Computer Science, Information Systems, Software or Electrical/Electronics Engineering, or a comparable field.
10+ years of professional software engineering experience, including 2+ years at staff level.
Demonstrated leadership of architecture decisions spanning multiple teams with concrete examples of driving cross-team technical direction to a decision.
Proven ability to drive technical outcomes across diverse stakeholders and teams that report into different functions, aligning divergent interests without direct authority.
Track record of owning significant initiatives end to end, including release ownership.
Strong proficiency in Python (working experience in Java a plus), building backend and cloud-based services.
Deep experience designing, building, and operating scalable, enterprise-grade distributed systems on AWS.
Strong data-modeling and service-architecture skills, with a track record of building durable, reusable abstractions that other teams adopt and extend without rework.
Experience designing backend systems that enable demanding workloads wih high-throughput data pipelines, asynchronous processing, or ML/inference services at scale and with cost-efficiently.
Solid grounding in application security and multi-tenancy: authentication/authorization, token handling, tenant isolation, and permission-aware data access.
Experience designing high-scale API contracts
Strong experience with infrastructure-as-code and CI/CD for cloud services.
Strong understanding of observability in distributed systems: logging, metrics, tracing, and alerting.
A demonstrated habit of staying current with rapidly evolving AI capabilities and integrating them into how you work and design.
Excellent written and verbal communication in English

Nice To Haves

Building services that support AI/ML product features and data pipelines
Integrating third-party SaaS platforms and connectors with attention to security and reliability.
Search and retrieval systems
Domain familiarity with CLM, contracts, or comparable enterprise B2B platforms.

Responsibilities

Own the canonical data models and service boundaries in your domain
Design models and boundaries that let independent systems evolve in parallel without duplicating logic or creating competing implementations
Evolve the platform through additive, backward-compatible changes that introduce new capabilities without disrupting existing behavior.
Own the architecture of one or more critical platform domains, with responsibility for design integrity, scalability, reliability, security, and long-term technical health.
Design AWS-native, event-driven and asynchronous services that scale on demand, degrade gracefully under load, and remain cost-efficient as volume grows.
Architect the backend to enable and support AI/ML workloads at scale with a focus on performance, scalability and cost efficiency.
Act as architectural steward for these services, keeping them scalable, resilient, secure, and maintainable as customer and platform demands grow.
Drive cloud-native design principles: stateless services, managed-service adoption, and failure-tolerant, self-healing architectures.
Treat tenant isolation, authentication, and authorization as first-class design concerns across every service and API you own.
Design secure authentication and token-handling flows, permission-aware data access, and safe credential management for an enterprise, multi-tenant platform.
Design for correct, isolated behavior across tenant, environment, and data-residency boundaries, and reason explicitly about security posture and blast radius when centralizing sensitive capabilities.
Partner with product- and engineering leaders to develop a deep understanding of customer and business needs and translate them into platform architectures that solve the problem
Lead the technical design of major platform initiatives end to end, and drive alignment across teams and functions whose priorities and incentives do not always converge.
Integrate diverse stakeholders and project teams around a shared technical direction, navigating differing functional interests with sound judgment and strong interpersonal skill.
Produce clear, rigorous design documents, service contracts, and acceptance criteria that others can review, build on, and trust, setting the standard for technical design on the team.
Use AI-assisted tools to accelerate and sharpen design and implementation, applying the judgment to know where they add leverage and where deeper thinking is required.
Lead by example in applying AI-assisted engineering tools to accelerate architecture, design, implementation, and testing, using sound technical judgment to amplify productivity without compromising quality, maintainability, or depth of thinking.
Design clean, versioned API contracts on top of the platform's data models — including high-scale bulk and asynchronous operations — with deterministic behavior, idempotency, structured error handling, and well-defined limits.
Establish contract tests and permission-enforcement validation as first-class parts of every API you design.
Own initiatives end to end from design through release, with accountability for product quality in your domain and high standards for reliability, security, observability, performance, scalability, usability, and cost across the services you own
Champion modern practices: infrastructure-as-code, automated testing, continuous delivery, and observability-by-default
Lead platform-modernization and refactoring initiatives while maintaining delivery velocity and improve the developer experience for the services you own.
Identify and drive improvements to how the engineering organization designs and delivers
Contribute across the stack when an initiative calls for it, including UI layers on top of the platform services you build; backend remains the primary focus.
Serve as a technical multiplier unblocking teams, accelerating architectural decisions, and reducing long-term complexity.
Partner with CloudOps, Security, MLOps, and integration teams to define reliability targets, operational-readiness standards, and clean interfaces between domains.
Mentor senior and mid-level engineers, raising the bar for data-model and systems design, security, and design-document quality.
Stay ahead of a fast-moving industry, particularly the rapid evolution of AI capabilities, and drive pragmatic adoption where it delivers clear business value.
Other duties as assigned.