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AI Architect

Bhrigu LLC
Remote

Quick apply

Job details

Full-time
7 days ago

Benefits

Internet reimbursement
Health insurance
Paid time off
Cell phone reimbursement
Work from home
Paid sick time

Qualifications

CI/CD
Image processing
Azure
Law
System design
Master's degree
AWS
Distributed systems
Terraform
Continuous integration
Kafka
Manufacturing
AI

Full job description

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

Work Location: Remote

Quick apply

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