Enter a job title or keyword
Head of AI Lab – Remote
Job Location:
Monthly Salary:
Posted:
7 July 2026 (30+ days ago)
Posted:
Application Deadline:
4 October 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
WHAT YOU WILL DO
We are establishing the 360F AI Lab an in-house function tasked withdesigning governing and shipping AI capabilities that materially change howfinancial advisors and insurers serve their clients. The Head of AI Lab is thesenior technical leader and architect of this function.
This is a role for someone who has built and operated AI systems insideregulated financial services. You will own the architectural directionsecurity posture cost discipline IP and knowledge handling and governanceframework of every AI capability that 360F deploys across APAC and the MiddleEast.
You will set the technical bar hire and lead the Labs engineersdecide what we build versus buy and stand behind those decisions in front ofregulators clients and the board. The role demands judgment honed over yearsof bridging legacy core systems and modern AI not enthusiasm for the latestframework.
RESPONSIBILITIES
Strategy &Architecture
Define and own the AI referencearchitecture for the360F platform including the boundaries betweensystems-of-record systems-of-engagement and the inference layer.
Set the technology roadmap forfoundation models agentic frameworks retrieval systems and ML Ops toolingwith explicit build-vs-buy reasoning.
Translate emerging AI capabilitiesinto a sequenced business-validated portfolio of investments rather than abacklog of experiments.
Security &Governance
Own the security posture of all AIsystems including prompt injection defenses agent permission scoping dataresidency and third-party model risk.
Establish 360Fs model riskmanagement framework: inventory tiering validation monitoring anddecommissioning aligned to MASTRM MAS FEAT PDPA and equivalent APACrequirements.
Embed responsible AI principleexplainability fairness human-in-the-loop boundaries and audit trails asdesign constraints not bolt-ons.
IP & Knowledge Handling
Set the policy and technicalcontrols for what proprietary data leaves the 360F perimeter under whatcontractual terms and to which model providers.
Design the institutional knowledgecapture layer how underwriting heuristics advisor scripts product rules andclaims precedents are codified into governed access-controlled corpora.
Own IP positioning around inputsoutputs fine-tuned weights and embeddings in coordination with Legal andclient contracts.
Cost & Engineering Discipline
Own the unit economics of every AIcapability the Lab ships per-inference cost retrieval cost agent run cost andthe tooling to monitor them in production.
Set the engineering standards forthe Lab: CI/CD for AI systems evaluation harnesses observability and the barfor what is allowed into production.
Make the hard calls on when AI isthe right tool and when a deterministic rule workflow or better-designed formis the correct answer.
Leadership &Delivery
Hire mentor and retain a smallsenior AI engineering team. Set the cultural bar for craft rigor andintellectual honesty.
Partner with Product EnterpriseArchitecture Compliance and client-facing teams to move capabilities fromconcept to production at speed.
Represent the AI Lab toregulators clients partners and the board bilingually fluent in deeptechnical detail and senior business language.
REQUIREMENTS
12 years in technology with atleast 7 inside insurance reinsurance or financial advisory cross policyadministration underwriting claims distribution or actuarial systems.
Track record of designing andshipping AI/ML systems in production within a regulated financial servicesenvironment not pilots or PoCs.
Demonstrated ability to bridgelegacy core systems and modern AI/cloud stacks. You know that integration anddata quality not models are where transformations actually fail.
Deep current expertise inGenerative AI architecture LLM selection RAG agentic orchestration(LangGraph LangChain AutoGen or equivalent) vector retrieval and thetrade-offs of fine-tuning vs. prompting vs. retrieval.
Strong AI security posture: promptinjection agent permission scoping data exfiltration and model supply-chainrisk with controls you have personally implemented.
Fluency with regulatoryrequirements like MAS TRM MASFEAT PDPA and the cross-border data flowrealities of operating across APAC and the Middle East.
FinOps discipline for AIworkloads. You can model unit economics across model tiers routing strategiesand context-window growth and you have killed projects that didnt pencil out.
Clear point of view on IPownership of inputs outputs fine-tuned weights and embeddings and how itinteracts with vendor contracts and open-source model licenses.
Practical experience standing upmodel risk management and responsible AI frameworks that survive externalaudit not slide review.
Has hired mentored and retainedAI engineers in a tight market. Attracts talent on craft and reputation notonly compensation.
Bilingual in the rare sensecredible with senior engineers on architecture and with CFOs CROs andregulators on risk cost and ROI.
Stays hands-on with thetechnology. Personally tests new models frameworks and tools as they releasebuilds prototypes regularly and forms first-hand opinions rather than relyingon vendor decks conference talks or team summaries.
Please submit your resume to
Required Experience:
Director
