Tech Lead (Solutions Architect + Applied AI Lead) - Digital Twin & Clinical AI
Компания: Human Intelligence
Город , Dnipro,
Зарплата:
Размещено: 2026-04-01 16:36:10
Описание
Design next-generation clinical AI & digital twin systems — senior-level solutions architect required
Title: Tech Lead (Solutions Architect + Applied AI Lead) — Digital Twin & Clinical AI — (Contractor)
Location & Work Model This is a fully remote, contract-based role supporting globally distributed teams. The role requires reliable working-hour overlap with teams operating across the Americas and European time zones, with strong English communication skills.
Base fee: USD $1,500–$2,500 / MONTH + Performance Incentive (Contractor — paid via Wise or bank direct deposit) Engagement type: Independent Contractor (retainer-based)
Who We Are
We build human-centric precision intelligence systems that power digital twins and clinical AI assistants. Our products run on secure, multi-tenant cloud platforms with sophisticated white-labeling, rigorous privacy practices, and advanced observability. Everything we ship must meet strict reliability, scalability, and safety standards.
Who You Are
You are an experienced technical architect who has delivered complex cloud systems and production LLM/agent functionalities. You understand multi-tenant system design, secure data ingestion pipelines, logging/metrics frameworks, SLA/SLO control, and AI safety/guardrail engineering. You mentor teams, improve platform quality, and operate with focus and independence. You pride yourself on attention to detail and excel in working environments that allow you to work independently on focused objectives.
Role purpose. Own end-to-end technical direction for the company’s AI-first products (Digital Twin, CLIA, wellness apps), spanning architecture, model lifecycle, data, security, reliability, and team technical excellence.
Core outcomes
Reliable, scalable production platforms (99.9%+ target SLOs) with cost-aware infra & observability.
Measurable AI/ML impact (e.g., model-enabled features that improve wellness outcomes, UX metrics, and conversion).
Responsible-AI guardrails in production (safety, bias, privacy, auditability) and compliant data flows.
Key responsibilities:
Architecture & Platform
Design multi-tenant, API-first, white-label architecture (B2B2C), event-driven integrations, and data mesh/warehouse patterns.
4+ years building prompt engineered pipelines using LangChain, ai orchestration tools, and AI LLMs including Gemini, Claude, GPTs and Grok.
At least 2+ projects involving Azure Container Apps, Azure Functions
Minimum qualifications
8–12+ years building cloud products; 3+ as Tech Lead/Architect; production experience with LLMs/agents.
Strong systems design, data platforms, API design, and security fundamentals.
Nice-to-have
Healthcare/wellness, regulated data (HIPAA/GDPR), on-device ML, voice agents, Xano/FlutterFlow ecosystems.
KPIs
Availability vs SLOs; time-to-restore; infra $/MAU; model quality lift; latency/p95; roadmap velocity; audit findings = 0 criticals.
Benefits
Compensation & performance bonuses Retainer: USD $1500 - $2,500 per month (adjustable by seniority and scope). Performance Incentive: Annual bonus for consistent KPI over-performance
Payment & contractor terms Independent Contractor status only. Payment in USD via Wise or bank direct deposit. Monthly retainer invoicing. Paid time off for exceptional performance.
How to apply • Provide two architecture diagrams and a 1–2 page ADR from prior work, plus a Loom walkthrough describing how you production-hardened an LLM feature. • Self-schedule a 16-minute AI-powered prescreen video. • Complete a 3rd-party personality profile. • If shortlisted, you will receive a small technical assignment. • Successful candidates will interview with a hiring manager within 24–48 hours — offers issued quickly for top performers. • Accelerated interview track available for exceptional applicants.
Closing note This position is reserved for senior engineers capable of architecting secure, scalable applied-AI platforms. Strong technical artifacts and real-world LLM experience are required.
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