Tech Lead (Platform Architect + Applied AI Engineer)- Digital Twin & Clinic at Shae Group

Special capital Region of Jakarta, Java, Indonesia -

Full Time

Start Date

Immediate

Expiry Date

18 Apr, 26

Salary

2500.0

Posted On

18 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Engineering, Platform Architecture, Cloud Systems, LLM Prompt Engineering, Multi-Agent Systems, Production Testing, Documentation, Technical Leadership, CI/CD, Software Delivery, Communication, Risk Management, Observability, Data Flows, Security Controls, Edge AI

Industry

Design Services

Description

Architect clinical AI and digital twin platforms — Senior Applied AI Lead Needed Title: Tech Lead (Platform Architect + Applied AI Engineer)- Digital Twin & Clinical Ai - Remote (Contractor) Location: Remote - Global - Philippines, Vietnam, Indonesia, China, Latin America (Mexico, Colombia, Brazil, Argentina, Peru, Ecuador), Eastern Europe (Poland, Ukraine, Romania, Bulgaria, Belarus, Lithuania), Africa (Kenya, South Africa, Nigeria, Ethiopia, Ghana, Egypt). Must have professional proficiency in spoken and written English. Base fee: USD $1500 - $2,500 / MONTH + Performance Incentive (paid via direct deposit) Employment type: Contractor (full-time retainer) Company: Shae Group Website: https://shae.group IF YOU SEE THIS POSTING THE JOB IS STILL ACCEPTING APPLICATIONS Role Overview Shae Group is hiring a senior Technical Solutions Architect / Tech Lead to drive architecture, technical direction, and delivery alignment for our clinical AI, conversational AI, and digital twin platform roadmap. This role is AI-native: every Tech Lead at Shae must have hands-on AI engineering experience, especially in LLM prompt engineering and agentic/multi-agent systems shipped to production. We are not looking for candidates whose “AI experience” is limited to basic prompting or a single chatbot release. You will act as the north star for technical execution: receiving product vision from leadership, translating it into technical architecture and documentation, keeping multiple teams aligned (including agency teams), and ensuring delivery stays on-track through strong communication, structured thinking, and rigorous quality standards. What You’ll Own1) AI Engineering Leadership (Non-Negotiable) Lead delivery of LLM-driven, conversational AI systems (not rule-based chatbots) Build and ship production-grade capabilities such as: Function calling / tool use / actions from conversation Multi-agent / agentic workflows and orchestration Prompt design patterns, testing, and evaluation approaches Ensure systems are production-hardened with: Robust testing and regression protection Safety/guardrails and failure handling Monitoring and performance controls Preference weighting (per hiring manager): Strongly prefer candidates with deep LLM prompt engineering experience (~70%) Fine-tuning experience is valuable but secondary (~30%); a few real projects can be sufficient Bonus “brownie points”: Experience deploying AI models/LLMs on the edge (edge inference / on-device / near-device constraints) 2) Platform Architecture & Cloud Systems (High-Level, Not Just App-Level) Own architectural thinking from the top down: Cloud services, system boundaries, data flows, security controls Design scalable foundations for: Multi-tenant systems White-label / configuration-driven product variants Secure data ingestion pipelines (including wearables → processing → insights) Observability (logs, metrics, tracing), incident readiness, reliability standards Define and enforce quality standards: CI/CD expectations, linting, automated tests “Definition of Done” for production readiness 3) Technical Direction, Documentation, and Alignment Convert vision into execution via strong written and visual artifacts: Architecture diagrams ADRs (Architecture Decision Records) Technical implementation plans and sequencing Use AI tools (e.g., GPT) to accelerate: Documentation drafting Meeting note synthesis → action items Ticket scaffolding and technical breakdowns Candidates who refuse to use AI tooling for productivity are not a fit for this role. 4) Delivery Leadership Across Multiple Teams Act as the technical “brain” partnering closely with a Project Manager (PM): PM handles admin/logistics; you ensure technical correctness + vision alignment Drive team alignment through: Tech lead presence in team syncs ~3x/week On-demand calls with developers to unblock, clarify, and correct course Ensure the right work is assigned to the right people: Identify skill gaps, resourcing risks, or delivery threats early Propose solutions, escalate for approval, and help roll changes out cleanly Maintain delivery integrity across internal and agency teams: Prevent drift from original vision Ensure code is in the correct repo/codebase and meets quality expectations What Success Looks Like Teams ship complex AI features that work reliably in production (not prototypes) Architecture is documented clearly and used consistently by developers Developers and PMs leave interactions with you feeling clear, calm, and confident Projects stay aligned to vision, with minimal drift across distributed teams Risks are surfaced early with structured options and clear recommendations Delivery quality is high: CI/CD healthy, testing solid, releases controlled and safe Required Skills & Experience (Must-Have) Senior-level engineering background (architecture + delivery leadership) AI engineering experience with evidence of shipping: LLM-driven conversational systems Agentic/multi-agent workflows Production testing, evaluation, and hardening Strong prompt engineering depth across multiple LLM providers/models Ability to architect at a systems level: Cloud services, security, data flows, reliability, observability Strong software delivery discipline: CI/CD, code quality, test strategy, release readiness Excellent written communication: Can produce structured, clear updates and decision docs quickly Professional English fluency + strong accent comprehension Must communicate clearly across multinational teams without repeated misunderstandings Calm, firm, outcomes-driven leadership style: Low ego, open-minded, but able to hold the line on standards and direction Ability to context-switch effectively across multiple projects and threads Preferred Skills (Nice-to-Have) Azure depth (especially Azure managed services) Machine learning background (helpful signal, not a strict requirement) Healthtech / regulated data environment experience Edge AI / edge inference deployments Voice agent experience, video integration, or advanced multimodal AI systems Vector databases / RAG architectures for clinical decision-support workflows Contract & Compensation Monthly retainer: USD $1,500–$2,500/month (adjusted by seniority/scope) Performance incentive: annual bonus for sustained KPI over-performance Paid via USD bank transfer Independent Contractor status Monthly invoicing Paid time off possible for exceptional performance How to Apply To apply, please submit: Two architecture diagrams from prior work One ADR (1–2 pages) showing how you document major technical decisions A short Loom walkthrough describing how you production-hardened an LLM/agent feature What failed in production? How did you test/evaluate? What guardrails did you add? How did you monitor and prevent regressions? Process: 16-minute AI prescreen video interview Third-party personality profile Small technical assignment (shortlisted candidates) Hiring manager interview within 24–48 hours Fast-track for exceptional applicants Closing Note This role is for senior candidates who can architect and lead delivery of applied AI systems with high standards. If your AI experience is limited to basic prompting or a simple chatbot, this will not be a fit.

Responsibilities

The Tech Lead will drive the architecture and technical direction for clinical AI and digital twin platforms, ensuring alignment and delivery across multiple teams. This includes leading the development of LLM-driven conversational AI systems and overseeing the technical execution of projects.