Senior Forward Deployed Engineer – AWS & Agentic AI

About CloudiQS

CloudiQS is an AWS Advanced Tier Services Partner specialising in cloud engineering, modernisation, security, managed services and artificial intelligence.

We are an AWS-only partner focused on helping customers build, protect, transform and operate production workloads.

Alongside our AWS consulting and managed services practices, we are developing CloudiQS Unify and our Agentic AI Bakery, providing reusable capabilities to build, deploy, manage and govern enterprise AI agents.

We are looking for a highly capable, hands-on Senior Forward Deployed Engineer to help establish our next generation of customer-facing AI engineering.

The Role

As a Senior Forward Deployed Engineer, you will work directly alongside customer engineering teams to understand complex business challenges, design technical solutions and deliver production-grade software on AWS.

You will own technical workstreams throughout the entire delivery lifecycle, from discovery and architecture to coding, deployment, monitoring and ongoing improvement.

You will combine the engineering depth of a Senior Software Engineer with the customer-facing capabilities of a Solutions Architect and the ownership mindset of a technical founder.

This is a hands-on engineering position, not a traditional Product Owner, project manager or purely advisory Solutions Architect role.

Key Responsibilities

1. Customer-Facing Engineering

• Embed directly with customers to understand their business workflows, technology architecture and operational challenges.
• Translate ambiguous requirements into clear technical designs and measurable outcomes.
• Collaborate with customer engineers, business stakeholders and CloudiQS delivery teams.
• Participate in technical discovery and solution scoping alongside AWS and CloudiQS commercial teams.

2. Build Production AI and Agentic Systems

• Architect, develop and deploy secure, scalable AI applications using Amazon Bedrock and other appropriate AWS services.
• Design intelligent agents, multi-agent workflows, retrieval pipelines, RAG systems, API integrations and workflow automation.
• Integrate foundation models with enterprise data, internal applications, APIs and existing business systems.
• Implement reliable agent orchestration, tool execution, identity controls, context management and error recovery.
• Optimise performance, latency, model usage and operating costs.

3. Own End-to-End Production Delivery

• Write production-quality code, primarily using Python and/or TypeScript.
• Build APIs, backend services, infrastructure and deployment pipelines.
• Use infrastructure as code and automated CI/CD pipelines.
• Develop testing, evaluation, observability, logging and alerting capabilities.
• Implement security, least-privilege access, auditability, guardrails and human approval controls.
• Troubleshoot production incidents, identify root causes and ensure effective operational handover.

4. Develop CloudiQS Reusable Engineering IP

• Convert customer delivery experience into reusable agents, connectors, skills, templates and reference architectures.
• Contribute engineering capabilities to CloudiQS Unify and the Agentic AI Bakery.
• Build repeatable AWS deployment patterns that accelerate future customer engagements.
• Work with product and engineering teams to identify components suitable for standardisation and commercial reuse.

5. Technical Leadership and Customer Growth

• Mentor engineers through code reviews, architecture discussions and pairing.
• Support technical presentations, demonstrations and customer solution validation.
• Identify opportunities to expand AI adoption and modernise existing AWS environments.
• Work with Managed Services teams to ensure solutions are supportable after deployment.
• Establish engineering standards aligned with AWS Well-Architected principles.

Essential Qualifications

• 5+ years of professional software engineering experience.
• Proven experience designing, developing and operating production software.
• Strong programming skills in Python and/or TypeScript.
• Practical experience deploying AI or LLM-based applications in production.
• Strong understanding of agentic systems, RAG, model evaluations, APIs and distributed application architecture.
• Hands-on AWS experience covering compute, networking, IAM, monitoring, security and automated deployments.
• Experience collaborating directly with customer stakeholders and technical teams.
• Ability to independently investigate technical issues, make architectural decisions and deliver complete solutions.

Preferred Qualifications

• Experience with Amazon Bedrock, Amazon Bedrock AgentCore and enterprise AI agent architectures.
• Experience with Model Context Protocol (MCP), multi-agent orchestration and enterprise system integrations.
• Experience using AWS Lambda, ECS/Fargate, API Gateway, S3, CloudWatch and related services.
• Experience with Terraform, CloudFormation or AWS CDK.
• Familiarity with enterprise security, governance, human-in-the-loop controls and AI evaluation frameworks.
• AWS Associate or Professional certification.
• Interest in achieving AWS Partner FDE Validated or Advanced credentials across the Ground, Orchestrate and Prove pathways.
• Experience in a consulting organisation, AWS Partner or fast-growing technology business.
• Previous experience mentoring engineers or leading customer delivery workstreams.

Success in the First 90 Days

We will assess success through working software, delivery quality and customer outcomes.

First 30 days: Understand CloudiQS architecture, engage with qualified customer opportunities, establish delivery standards and demonstrate an initial AWS AI solution.

Days 31–60: Own delivery of a customer AI implementation or production-ready pilot, including testing, security and operational readiness.

Days 61–90: Produce a further customer deliverable, contribute at least one reusable engineering component and demonstrate measurable improvements in customer delivery effectiveness.

What Makes You Successful

You enjoy solving real customer problems rather than working exclusively from predetermined specifications.

You are equally comfortable discussing requirements with senior stakeholders, reviewing architecture, writing code and investigating a production incident.

You take ownership of the outcome, not simply the task assigned.

You know the difference between an impressive AI demonstration and a secure, reliable production system.

Why Join CloudiQS?

• Help establish a founding Forward Deployed Engineering capability within an AWS-only partner.
• Work directly with customers and AWS teams on production AI projects.
• Influence the development of CloudiQS Unify and the Agentic AI Bakery.
• Build reusable technology rather than repeating one-off implementations.
• Play a key role in expanding CloudiQS’s AI engineering and managed-services businesses.

Application Process

Please submit your CV or professional profile, together with a short description of an AI or software solution you personally designed and delivered into production.

We are particularly interested in the architecture, the code you developed, the challenges you solved, the production controls you implemented and the measurable business outcome.

Our recruitment process will include technical discussions, a practical engineering assessment and a customer-focused architecture scenario.

Pay: £62,500.00-£120,000.00 per year

Work Location: Remote

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