Note: The job is a remote job and is open to candidates in USA. JLL is a global provider of real estate and investment management services that is building an internal AI platform for employees and teams across the firm. The Staff Software Engineer will set technical direction, build and operate distributed platform systems and model gateways, and solve AI engineering challenges involving evaluation, guardrails, cost, latency, and reliability. The role also includes establishing platform standards, supporting integrations, mentoring engineers, and documenting durable designs.
Responsibilities
- Own significant parts of the platform end to end, from the shape of the API through to how it behaves under load
- Be accountable for reliability and performance in production, on a gateway that sits on the critical path of everything the firm builds with AI
- Design the model gateway: provider abstraction, routing, failover, and making a provider switch a configuration change rather than a migration
- Make the agent surface work regardless of which framework a team chose or where their agent runs
- Build the evaluation and benchmarking capability the platform needs, largely from scratch
- Design the guardrails that let an agent reach production safely, and help turn draft internal standards into something enforceable in code
- Own inference cost and latency as first class engineering concerns, including spend attribution and the routing decisions behind it
- Keep pace with a model landscape that changes weekly, and make onboarding a new model routine rather than a project
- Make the compliant path the fast path, so that building on the platform is how a team clears architecture, security and responsible-AI review
- Be the engineer other teams bring their hardest integration problems to
- Raise the bar on observability before scale forces the issue
- Mentor across a distributed team, and leave behind designs and documentation that outlast your involvement
Skills
- 8+ years building and operating production systems
- Direct experience shipping agentic systems to production, not prototypes: agentic patterns, retrieval, tool calling, inference cost and latency, etc
- Hands-on experience with more than one model provider, including dealing with the differences between them in practice
- Experience with evaluation, observability or guardrail tooling for agentic systems
- Strong platform engineering track record, on systems where other engineering teams were your users
- Hands-on depth in at least one major public cloud, including running and debugging production workloads
- Experience designing APIs and abstractions that others build against and that you then have to keep stable
- Demonstrable production ownership: on-call, incident response, root cause analysis
- A track record of pushing work through a large organisation: navigating process, winning the argument, and getting decisions unblocked rather than waiting on them
- Excellent English communication, written and spoken
- This position does not provide visa sponsorship. Candidates must be authorized to work in the United States without sponsorship
- Built or operated an internal developer platform or shared multi-tenant service
- Kubernetes and container-based delivery
- Infrastructure as code
- Enterprise security, data privacy or responsible-AI review processes
Benefits
- 401(k) plan with matching company contributions
- Comprehensive Medical, Dental & Vision Care
- Paid parental leave at 100% of salary
- Paid Time Off and Company Holidays
- Early access to earned wages through Daily Pay
Company Overview