Lead Engineer - Agentic AI Platform (AWS, Bedrock, Multi-Tenant Control Plane)

CloudiQS

2 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Languages

English

Experience level

Senior

Compensation

£ 106K

Job location

Remote

Tech stack

Artificial Intelligence

Amazon Web Services (AWS)

Automation of Tests

Software as a Service

Amazon DynamoDB

Identity and Access Management

Python

Node.js

Next.js

Systems Integration

TypeScript

Management of Software Versions

Data Logging

Data Ingestion

React

Large Language Models

Backend

Amazon Web Services (AWS)

Machine Learning Operations

Front End Software Development

Api Design

Cloudwatch

Legacy Systems

Microservices

Job description

CloudiQS is exiting that we are building a next-generation agentic AI control plane for enterprises and consulting partners. This platform will allow organisations to:

Build, configure, and version AI agents
Integrate data sources, tools, and AWS services
Deploy agents into enterprise AWS accounts
Monitor cost, performance, compliance, and behaviour
Manage agent lifecycle end-to-end (design * configure * test * deploy * monitor)

You will be the technical owner and Lead Engineer responsible for architecting and building the platform from the ground up.

This is NOT a basic chatbot builder - this is a full enterprise-grade AgentOps platform, aligned with AWS Bedrock AgentCore, multi-provider LLM routing, secure multi-tenant deployments, and deep observability into agent cost and behaviour., * Design and implement the multi-tenant agent control plane on AWS

Build backend microservices for:
Agent creation wizard
Agent Studio (configuration, prompts, tools, data, memory, security, grounding)
Model selection & cost optimisation
Data ingestion pipelines (S3, DynamoDB, RDS, Connectors)
Deployment engine (ECS/Lambda/EKS)
Monitoring, logging, and audit events
Implement LLM Gateway / LiteLLM for multi-provider routing (Bedrock, OpenAI, Anthropic)

Frontend / UX

Build clean, modular, React-based interface with:
Workspace + agent library
Agent creation wizard (multi-step, AI-assisted)
Agent Studio tabs (Model, Knowledge, Data Sources, Tools, Memory, Security, Advanced)
Test & validation playground
Deployment dashboard
Monitoring dashboard (tokens, cost, latency, failures)

AWS Integration

You must be deeply experienced with:

Amazon Bedrock (models, guardrails, knowledge bases, agents)
IAM & KMS for granular agent permissions
Lambda, Step Functions, ECS for runtime orchestration
DynamoDB, S3, RDS for agent data + metadata
CloudWatch & CloudTrail for observability and auditing
Cognito for workspace identity management

Bonus:

Experience implementing multi-provider model gateways
Experience integrating LiteLLM or similar (smart routing, cost controls)

Agent Lifecycle (Core Capability)

You will design and implement:

Agent versioning
Rollback workflow
Deployment approval workflow
Automated testing:
latency, correctness, grounding, guardrail hits
Compliance and audit reporting
Cost optimisation logic

Security & Compliance

Build enterprise-grade security features:

PII detection
Guardrails configuration
IAM policy generation
Encryption at rest and transit
Audit logs, activity monitoring
Regional data residency, As the Lead Engineer, you will help design and deliver:
An internal control plane for building and shipping agents
A marketplace-ready platform that customers can deploy inside their own AWS account
A partner-ready system for AWS and consulting partners

This is an opportunity to build one of the most advanced agent lifecycle and deployment platforms on AWS today.

Why Work With Us?

You own the architecture
You work directly with founders
No legacy systems - greenfield AI platform
Massive market demand (enterprise AI agents + governance)
Opportunity to build a flagship product in the Agentic AI ecosystem

Requirements

Do you have experience in TypeScript?, Do you have a Master's degree?, Required Skills: Technical (Must-Have)

Expert in AWS architecture (5+ years) Deep knowledge of Amazon Bedrock Experience with LLM systems, agents, RAG, memory Strong backend engineering with Python or Node.js Frontend capability (React, Next.js, TypeScript) Experience building enterprise SaaS platforms Strong understanding of: