Staff Software Engineer - AI
Job Description
At Future Secure AI, we're building something genuinely new — and we're looking for people bold enough to build it with us. We work at the frontier of AI, tackling big, real‑world problems for global enterprises across multiple industries, armed with state‑of‑the‑art technology and a culture that prizes courage, rigor, and relentless curiosity.
Future Secure AI (FSAI)\nFSAI is a leading enterprise AI company created in deep partnership with one of the world’s largest financial institutions. Operating as an enterprise company with deep relationships at the C‑suite level, FSAI believes humans and AI workers will collaborate seamlessly to raise organisational performance.
The role\nYou’ll own the end‑to‑end technical delivery of AI Co‑Workers from concept through to enterprise production deployment. You’ll work closely with Engagement Leads to keep technical execution tied to business outcomes, and you’ll be the person engineers look to when a build gets complex.
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- Lead architecture and implementation of AI Co‑Workers across models, APIs, orchestration, data pipelines, and integrations \n
- Write production‑quality Node.js and TypeScript on the critical path; this is not a pure management role \n
- Own technical decisions around LLM selection, prompt design, evaluation, and monitoring \n
- Guide engineers through build, test, and release cycles \n
- Translate enterprise business constraints into scalable, maintainable engineering solutions \n
- Identify technical risks early and drive pragmatic solutions in ambiguous environments \n
- Communicate clearly with non‑technical stakeholders at enterprise level \n
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- Proven track record leading engineering teams shipping real products into enterprise environments \n
- Strong hands‑on Node.js and TypeScript skills — you own the codebase, not just the pull request reviews \n
- Solid applied AI experience: LLMs, intelligent automation, or production ML systems \n
- Deep understanding of backend systems, APIs, data flows, and production architecture at scale \n
- Ability to reason across accuracy, latency, cost, scalability, and delivery speed \n
- A bias toward ownership and closing loops \n
- Curiosity about how AI systems behave in production, not just in theory \n
You’ll have real ownership of systems that run inside some of the most complex enterprise environments in the market. You’ll work with a high‑performance team on problems that matter, with the technical freedom to solve them properly. Competitive salary, meaningful equity, and a growth trajectory that matches the pace of the industry we’re building in.
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