Description

Role purpose

The FDE Supporting Engineer is a hands-on supporting engineer who turns the engagement’s target architecture into working,

verified software. This is not an entry-level coding role. The person brings strong full-stack execution and AI-assisted or agentic

engineering capability, owns defined workstreams, and works closely with the FDE Lead to deliver production-minded

outcomes while developing broader architecture and client leadership skills.

What you will own

 Build and integrate product capabilities across frontend, backend, APIs, data, cloud, automation, and AI-enabled

components.

 Translate target-state designs and technical requirements into maintainable code, configurations, tests, deployment assets,

and engineering documentation.

 Own assigned features, services, microflows, migrations, agents, or automations from implementation through verification

and release readiness.

 Use AI-assisted development tools and agentic workflows responsibly, including evaluation, test coverage, traceability, and

detection of over-execution or drift.

 Contribute to solution design, provide implementation feedback, identify constraints, and escalate risks or dependencies

early.

 Participate professionally and clearly in technical working sessions, demos, reviews, and handover activities as required.

 Apply secure development, CI/CD, observability, reliability, and operational practices appropriate to the solution.

 Learn rapidly across unfamiliar technologies and domains while maintaining engineering quality and delivery discipline.

Core qualifications

 Strong hands-on software engineering experience with evidence of building and shipping end-to-end application

capabilities.

 Full-stack depth across modern frontend, backend, API, data, and cloud components, with the ability to explain

implementation decisions beyond a single layer.

 Practical experience using AI-assisted development tools, LLM APIs, or agent frameworks to build working artifacts rather

than only exploratory demonstrations.

 Understanding of system design, integration, cloud deployment, security, testing, and operational concerns sufficient to

execute effectively within a target architecture.

 Ability to own a defined delivery scope, work with limited supervision, communicate constraints honestly, and collaborate

closely with Lead engineers and stakeholders.

 Strong debugging, testing, verification, and problem-solving skills, with attention to maintainability and evidence of quality.

 Clear written and verbal communication for engineering collaboration and technical working sessions.

Technical capabilities

 Application engineering: hands-on capability in one or more of Java, Python, .NET, JavaScript/TypeScript, Node.js, React,

Angular, or comparable technologies.

 APIs and integration: REST or GraphQL, microservices, event-driven patterns, database integration, and distributed

application fundamentals.

 Cloud and delivery: Azure, AWS, or GCP; containers; CI/CD; Git; Infrastructure as Code; observability; and automated

testing or deployment practices.

 AI engineering: LLM APIs, prompt engineering, RAG, vector databases or search, evaluation and verification, and

frameworks such as LangChain, LangGraph, Semantic Kernel, LlamaIndex, CrewAI, or AutoGen.

 Data: SQL and modern data concepts, ETL or ELT, streaming or analytics exposure, and the data flows required to support

applications and AI use cases.

 Security: secure coding, secrets handling, authentication and authorization, encryption basics, dependency hygiene, and

responsible AI practices.

Success indicators

 Assigned capabilities are delivered as working, tested, and supportable software.

FDE Lead & Supporting Engineer Profiles | Talent Acquisition Pack

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 Implementation risks, dependencies, and quality concerns are identified early and communicated clearly.

 AI-generated or AI-assisted outputs are verified rather than accepted without evidence.

 The engineer demonstrates growth in architecture reasoning, independent ownership, and client-ready communication.

Preferred experience

 Participation in modernization, migration, cloud-native, data, or AI-enabled product delivery.

 Hands-on contribution to proofs of concept that progressed into hardened software, reusable accelerators, or production

delivery.

 Experience working in agile or cross-functional teams spanning product, design, QA, platform, security, and client

engineering

Key Skills

Education

Any Graduate