Job Description

About the Role

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.

Key Responsibilities 1. Platform Architecture & Backend

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)

2. 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)

3. 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)

4. 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

5. 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

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:

Multi-tenant architectures Authorisation models Event-driven systems API design Observability & monitoring

Nice to Have

Experience with

LangChain, CrewAI, AgentCore, or similar agent frameworks

Experience in

cost optimisation

for AI workloads Knowledge of

MLOps or AIOps pipelines

Worked with

consulting teams or enterprise customers

What You Will Build

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

How to Apply

Send your CV + GitHub + portfolio to:

jobs@cloudiqs.com

Job Type: Full-time

Pay: 70,027.13-106,004.17 per year

Work Location: Remote