Senior AI Engineer - Data Science
About the job
- A bachelor's degree in Mathematics, Statistics, Computer Science, or a related field is required.
- At least 5 years of experience as a Data Scientist with hands-on experience and a track record of delivering impactful machine learning and artificial intelligence outcomes is required.
- Experience within the artificial intelligence sector is required.
- Experience with natural language processing techniques, including long short-term memory networks, convolutional neural networks, transformers, topic modeling, and supervised natural language processing, is required.
- Commercial experience with modern large language model ecosystems, including LangChain, LlamaIndex, retrieval-augmented generation pipelines, multi-agent frameworks, and GPT-based systems, is required.
- Python experience focused on machine learning and natural language processing is required.
- The ability to translate complex technical concepts into clear, actionable insights for non-technical stakeholders is required.
- Empathy, humility, openness to feedback, collaboration, and a growth mindset are required.
- Comfort working in an agile, fast-evolving environment is required.
- Architect, build, and deploy machine learning models and large language model systems for products and users.
- Analyze complex, large-scale structured and unstructured datasets to uncover insights and opportunities.
- Enhance large language model output quality across diverse use cases, including optimization of multi-step reasoning chains.
- Lead MLOps initiatives, including model performance tracking, benchmark design, quality assurance, and compliance.
- Influence long-term data and artificial intelligence strategy, including governance, ethical artificial intelligence, and scalable frameworks.
- Collaborate with engineering, product, and executive stakeholders to deliver innovative, production-ready solutions.
- Mentor and uplift junior data scientists and set standards for excellence.
- A master's degree or doctorate in Data Science, Mathematics, Statistics, Computer Science, or a related field is preferred.
- Knowledge of software languages in addition to Python is preferred.
About the company
Future Secure AI builds persona-based, multi-agent AI Co-Workers designed for large enterprises and private equity firms. Their core offering, Red-Zone AI Co-Workers, consists of over 100 agent personas that automate complex, high-stakes workflows. The agents integrate with a client’s core systems and governance frameworks and operate securely on the client’s network, remaining cloud- and LLM-agnostic to avoid vendor lock-in. Workflows run within a hybrid team, with AI Co-Workers reporting to human managers and maintaining human-in-the-loop oversight. The company differentiates itself by targeting mission-critical environments with on-premise deployment, strong governance, and integration into existing IT and security controls, rather than generic AI tools. Their stated goal is to deliver 10x to 20x ROI on operating costs, often paying for themselves within six months. Clients span infrastructure, services, finance, health, and connected economies.
Company Size
201-500
Company Stage
N/A
Total Funding
N/A
Headquarters
N/A
Founded
N/A
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Simplify's Take
What believers are saying
- September 2026 pre-IPO fundraising reached a $1.8 billion valuation cap.
- April 2026 Austin HQ and triple-hiring plan signal aggressive scaling.
- Customers cite Macquarie, Healius, FIS, and Toga for finance and operations wins.
What critics are saying
- ServiceNow and Salesforce shipped agent platforms in 2026, compressing differentiation quickly.
- September 2026 TTAB appeal shows trademark vulnerability around Future Secure AI branding.
- Multi-agent systems raise security and cascading-failure risks across privileged enterprise systems.
What makes Future Secure AI unique
- Red-Zone AI targets complex, mission-critical workflows beyond copilots or simple agents.
- On-network, cloud-agnostic deployments with 100+ agents reduce lock-in for regulated enterprises.
- Persona-based co-workers report to human managers, fitting hybrid enterprise teams and governance.
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Benefits
- Flexible Work Hours