ABOUT US
We are a US-based startup building next-generation software platforms for regulated life sciences manufacturing and laboratories. Our products operate in GxP-regulated environments, requiring strong engineering discipline, validation readiness, and security-by-design.
Here, you won’t just be a cog in the machine — you’ll be part of building the machine. If you thrive in environments where you can wear multiple hats, roll up your sleeves, and see your work through from start to finish, this is your opportunity to make a real impact.
We’re creating a culture of builders, thinkers, and problem-solvers who aren’t afraid to challenge the status quo. Your voice will be heard, your ideas will matter, and your contributions will shape the future of our product and the industry.
We’re growing fast, and looking for a hands-on Full Stack Development Lead – Life Sciences who’s ready to wear multiple hats and shape the future of digital pharma.
WHAT YOU WILL DO
As AI Architect, you will own the end-to-end design and delivery of the platform's AI/ML capabilities — from OT edge inference on constrained hardware to cloud-scale LLM-augmented workflows, computer vision for shopfloor quality, and an AI governance layer that satisfies FDA 21 CFR Part 11, EU Annex 11, and emerging AI-in-GxP guidance (GAMP 5, FDA AI/ML framework).
DUTIES AND RESPONSIBILITIES:
AI Platform Architecture
- Design a three-horizon AI maturity roadmap: rule-based decision support → supervised ML → autonomous orchestration
- Architect a tenant-isolated AI inference layer using per-tenant KMS CMKs and namespace-level isolation
- Define the Unified Namespace (UNS) + MQTT Sparkplug B data spine for AI-ready OT/IT convergence
- Lead selection and governance of LLM, embedding, and vision model stack (open-weight vs. proprietary)
GxP AI Governance
- Design the AI Model Lifecycle Management (MLM) framework covering versioning, validation, drift monitoring, and retirement under 21 CFR Part 11 / Annex 11
- Author AI Risk Assessment documents aligned with GAMP 5 Category 4/5 and FDA AI/ML Action Plan
- Implement immutable audit trails for all AI-generated records, predictions, and human-override events
- Define Algorithm Change Protocol (ACP) procedures for post-market model updates without full revalidation
LLM & Intelligent Workflow
- Integrate LLM-augmented workflows into various modules using modern AI + LiteLLM abstraction
- Build a retrieval-augmented generation (RAG) pipeline with pgvector for regulatory needs,
- Design multi-agent orchestration patterns for GxP-compliant AI-assisted review and approval workflows
- Implement prompt governance, hallucination detection, and output confidence scoring for regulated use cases
Computer Vision & Edge AI
- Architect vision AI pipeline for Presence/Absence, Count, and Read detection in manufacturing environments
- Design edge inference stack
- Define synthetic dataset generation workflows for GxP-compliant training data governance
Data & MLOps
- Own the ML feature store design using TimescaleDB continuous aggregates
- Build MLOps pipeline: experiment tracking (MLflow/W&B) → CI/CD model promotion → canary deployment → rollback
- Implement model observability: prediction drift, data quality, SLA alerting integrated with the platform's alarm subsystem
WHAT YOU WILL BRING
Experience
- ·Minimum of 8 years total experience
REQUIRED TECHNICAL SKILLS
- 8+ years in software/data/ML engineering; 3+ as architect
- Production LLM system design (RAG, agents, fine-tuning)
- MLOps: experiment tracking, model registry, CI/CD pipelines
- Distributed systems: Kafka, event-driven architecture, EKS
- Time-series data: TimescaleDB, InfluxDB, feature engineering
- Computer vision: YOLO, SAM, CLIP/SigLIP, or equivalent
- Edge inference: TFLite, ONNX Runtime, quantization
- IaC: Terraform; cloud: AWS or Azure at scale
REQUIRED DOMAIN & REGULATORY REQUIREMENTS
- GxP/FDA 21 CFR Part 11 / EU Annex 11 compliance
- GAMP 5 Category 4/5 validation lifecycle
- OT/IT: MQTT Sparkplug B, ISA-95, SCADA/MES integration
- Ignition SCADA or equivalent industrial platform
- Industrial protocols: EtherNet/IP, Modbus, OPC-UA
- Multi-tenant SaaS: tenant isolation, per-tenant KMS
- Temporal workflow orchestration
- Pharmaceutical manufacturing domain knowledge
Why Join Us (vs. a Big Company)??
· True Ownership– You’ll help design and build a platform from the ground up. Every feature, every decision, every improvement — you’ll be part of it.
· Mission-Driven Work– We’re solving critical problems in pharma manufacturing that improve safety, compliance, and efficiency.
· Accelerated Growth– With us, you’ll learn faster, stretch your skills, and take on challenges that would take years to access elsewhere.
· Startup Energy, Real Impact– No red tape. No silos. Just smart, motivated people building something meaningful together.
· End-to-End Visibility– Be part of the full journey — from whiteboard to deployment — and actually see how your work changes the game.
- Build category-defining productsfor regulated life sciences
- Work on cutting-edge AI + vector searchin real-world GxP environments
- High ownership, real impact, and direct collaboration with US leadership
- Opportunity to influence platform architecture from early stages
Why You’ll Love It Here??
Here are some things you will be a part of:
· Build foundational products with real-world impact in life sciences.
· Work directly with founders and be part of early product leadership.
· Flexible remote work, async-friendly culture.
· Competitive equity, startup perks, and growth opportunities.
· Help define the culture of a product-first, purpose-driven startup.
Job Type: Full-time
Benefits:
- Cell phone reimbursement
- Health insurance
- Internet reimbursement
- Paid sick time
- Paid time off
- Work from home
Application Question(s):
- Are you currently an AI Engineer?
Work Location: Remote
