Description

Role purpose

The FDE Lead is the primary technical leader in the client environment. This person combines architecture judgment, hands-on

full-stack depth, AI-assisted engineering fluency, and stakeholder command to shape and deliver high-impact solutions. The

role owns the target-state direction, determines what the team can responsibly commit to, and maintains technical credibility

from the first conversation through delivery and handover.

What you will own

 Lead technical discovery and translate business priorities, constraints, and success measures into an executable solution

approach.

 Own target-state architecture, key design decisions, dependencies, deployment models, security considerations, and

engineering trade-offs.

 Act as the primary technical interface for client executives, architects, product leaders, engineering teams, and

stakeholders with decision or veto authority.

FDE Lead & Supporting Engineer Profiles | Talent Acquisition Pack

2

 Shape commitments, challenge assumptions constructively, and push back when scope, feasibility, risk, or evidence does

not support a responsible commitment.

 Drive delivery end to end in ambiguous environments, including planning, build oversight, validation, release readiness,

and outcome measurement.

 Remain technically hands-on and able to go deep across frontend, backend, APIs, data, cloud, CI/CD, observability, and

AI-enabled components as required.

 Guide engineers, review solution quality, remove technical blockers, and establish practical engineering standards for the

engagement.

 Ensure solutions are secure, scalable, resilient, supportable, and appropriately documented for transition to client or

product teams.

Core qualifications

 Demonstrated ownership of complex software delivery, modernization, migration, platform, or AI-enabled initiatives from

architecture through production outcomes.

 Strong system-level thinking, including the ability to reason about target state, integration, performance, scalability,

security, deployment, and operational trade-offs.

 Hands-on full-stack engineering experience across multiple layers, with depth in at least one modern application stack and

credible breadth across the remaining layers.

 Practical experience with AI-assisted development, LLM APIs, agentic workflows, evaluation, verification, and controls for

model or agent drift.

 Proven client-facing or stakeholder-facing leadership, including the ability to establish credibility, handle challenge,

communicate risk, and align diverse decision-makers.

 Independent delivery ownership with a record of operating effectively when requirements, data, stakeholders, or solution

paths are initially unclear.

 Clear written and verbal communication, with the ability to explain technical decisions in business and engineering terms.

Technical capabilities

 Application engineering: Java, Python, .NET, JavaScript/TypeScript, Node.js, React, Angular, or comparable modern

technologies.

 Architecture and integration: REST or GraphQL APIs, microservices, event-driven architectures, enterprise integration,

distributed systems, and modernization patterns.

 Cloud and platform: Azure, AWS, or GCP; cloud-native and serverless services; containers and Kubernetes; scalable and

resilient platform design.

 DevSecOps and automation: CI/CD, GitOps, Infrastructure as Code such as Terraform or Ansible, observability,

monitoring, release engineering, and Secure SDLC.

 AI and data: Generative AI, machine learning, RAG, vector stores or search, orchestration frameworks, prompt

engineering, LLMOps, data pipelines, analytics, and secure AI practices.

 Security and governance: identity and access management, Zero Trust concepts, encryption and key management,

compliance-aware design, and architecture governance.

Success indicators

 Technical credibility is established early with client architects and leadership.

 The engagement has a clear target state, explicit trade-offs, accountable decisions, and measurable outcomes.

 Commitments are realistic, risks are surfaced early, and the team delivers usable, verified software.

 Engineering quality and knowledge transfer allow the solution to progress beyond the initial engagement.

Preferred experience

 Leadership of proof-of-concept, accelerator, modernization, cloud transformation, or AI transformation engagements.

 Experience across one or more regulated or enterprise environments where security, integration, and governance

materially influence design.

 Architecture frameworks or certifications such as TOGAF, cloud architecture, security, data, or AI credentials. Certifications

are helpful but not a substitute for demonstrated delivery

Key Skills

Education

Any Graduate