Asks for

The ad says“AI agents, intelligent automation, and prompt engineering”
The ad says“AI-assisted development workflows and tooling”
The ad says“Anthropic / Claude — enterprise AI integration, Claude API, responsible AI workflows”
The ad says“Enterprise Solution Architecture, Microservices, Event-Driven and API-first design”
The ad says“Azure / AWS / GCP — cloud-native architectures, managed services, IAM, networking”
The ad says“Azure / AWS / GCP — cloud-native architectures, managed services, IAM, networking”
The ad says“Modern software engineering, DevOps, CI/CD pipelines”
The ad says“Cloud-native systems, distributed architectures, integration patterns”
The ad says“Databricks — unified data and AI platform, Delta Lake, MLflow, notebooks”
The ad says“Databricks — unified data and AI platform, Delta Lake, MLflow, notebooks”
The ad says“Modern software engineering, DevOps, CI/CD pipelines”
The ad says“Cloud-native systems, distributed architectures, integration patterns”
The ad says“Docker / containerised deployments, cloud-managed compute and serverless patterns”
The ad says“Enterprise Solution Architecture, Microservices, Event-Driven and API-first design”
The ad says“Enterprise Solution Architecture, Microservices, Event-Driven and API-first design”
The ad says“FastAPI / Python frameworks — API development, backend services, AI application scaffolding”
The ad says“Azure / AWS / GCP — cloud-native architectures, managed services, IAM, networking”
The ad says“Generative AI platforms and Large Language Models (LLMs)”
The ad says“GitHub / Git — version control, branching strategies, pull request workflows, CI/CD integration”
The ad says“GitHub / Git — version control, branching strategies, pull request workflows, CI/CD integration”
The ad says“Cloud-native systems, distributed architectures, integration patterns”
The ad says“AI agents, intelligent automation, and prompt engineering”
The ad says“Generative AI platforms and Large Language Models (LLMs)”
The ad says“Enterprise Solution Architecture, Microservices, Event-Driven and API-first design”
The ad says“Databricks — unified data and AI platform, Delta Lake, MLflow, notebooks”
The ad says“Observability, reliability engineering, and testing strategies”
The ad says“OpenAI API (GPT-4 and beyond) — prompt engineering, function calling, embeddings”
The ad says“AI agents, intelligent automation, and prompt engineering”
The ad says“Python, modern application frameworks, API-based architectures”
The ad says“Observability, reliability engineering, and testing strategies”
The ad says“Security-by-design, scalability and resilience principles”
The ad says“Snowflake — cloud data warehousing, data sharing, and analytics at scale”
The ad says“Observability, reliability engineering, and testing strategies”

Edelman is a voice synonymous with trust, reimagining a future where the currency of communication is action. Our culture thrives on three promises: boldness is possibility, empathy is progress, and curiosity is momentum.

At Edelman, we understand diversity, equity, inclusion and belonging (DEIB) transform our colleagues, our company, our clients, and our communities. We are in relentless pursuit of an equitable and inspiring workplace that is respectful of all, reflects and represents the world in which we live, and fosters trust, collaboration and belonging.

Technical Solutions Lead

Client Services & Platform

SUMMARY

A technically sharp and commercially curious Solution Architect with a strong foundation in enterprise technology design, AI integration, and hands-on software delivery. Comfortable bridging the gap between business needs and technical execution — designing practical, scalable solutions while staying close to the code.

Brings experience across consulting, rapid prototyping, and multi-system architecture, with a genuine enthusiasm for the opportunities that generative AI and modern engineering practices unlock for clients and teams.

PROFESSIONAL EXPERIENCE

Solution Architecture & Technical Design

Design and document end-to-end solution architectures aligned to business requirements, security, and scalability.
Contribute to reference architectures and architectural patterns across project engagements.
Evaluate and recommend technology stacks — including AI platforms and development tooling — with clear rationale.
Support architecture reviews and ensure solutions align with enterprise standards and governance requirements.

Engineering Delivery

Work closely with engineering teams to translate architecture into working, production-quality systems.
Apply modern engineering practices: clean code, CI/CD pipelines, testing strategies, and observability.
Participate in code and design reviews, sharing architectural context and raising quality across the team.
Comfortable getting hands-on — contributing code and debugging when it matters most.

Rapid Prototyping & AI Innovation

Lead proof-of-concept builds to de-risk architecture decisions and validate solution approaches quickly.
Use AI-assisted development tools (coding copilots, LLM APIs, agent frameworks) to accelerate delivery and exploration.
Translate prototype learnings into well-structured, production-ready architectures and delivery plans.
Stay current with the fast-moving generative AI landscape and bring relevant ideas to client engagements.

Consulting & Stakeholder Engagement

Engage directly with business and technical stakeholders to understand requirements and shape practical solutions.
Support workshops, solution design sessions, and technical discovery activities.
Communicate architectural thinking clearly — adapting the level of detail for different audiences.
Contribute to proposals, assessments, and solutioning work as part of client engagements.

TECHNICAL CAPABILITIES

Architecture & Design

Enterprise Solution Architecture, Microservices, Event-Driven and API-first design
Cloud-native systems, distributed architectures, integration patterns
Security-by-design, scalability and resilience principles

Artificial Intelligence & Emerging Technology

Generative AI platforms and Large Language Models (LLMs)
AI agents, intelligent automation, and prompt engineering
AI-assisted development workflows and tooling

Engineering & Delivery

Modern software engineering, DevOps, CI/CD pipelines
Observability, reliability engineering, and testing strategies
Rapid prototyping and proof-of-concept development
Python, modern application frameworks, API-based architectures

WHAT SETS THIS ROLE APART

You'll work at the intersection of architecture, AI, and consulting — not siloed in one discipline.
Real exposure to generative AI in enterprise settings — not just theory, but hands-on delivery.
Mentorship and growth from senior technology and business leadership while owning meaningful pieces of complex client solutions.
A culture that values engineering quality, intellectual curiosity, and getting things built.

TOOLS & PLATFORMS

AI & Language Models

OpenAI API (GPT-4 and beyond) — prompt engineering, function calling, embeddings
Anthropic / Claude — enterprise AI integration, Claude API, responsible AI workflows

Data & Analytics

Databricks — unified data and AI platform, Delta Lake, MLflow, notebooks
Snowflake — cloud data warehousing, data sharing, and analytics at scale

Cloud & Infrastructure

Azure / AWS / GCP — cloud-native architectures, managed services, IAM, networking
Docker / containerised deployments, cloud-managed compute and serverless patterns

Development & Source Control

GitHub / Git — version control, branching strategies, pull request workflows, CI/CD integration
FastAPI / Python frameworks — API development, backend services, AI application scaffolding

EDUCATION

Bachelor's Degree in Computer Science, Software Engineering, or a related technical discipline — or equivalent practical experience.

We are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role but your experience doesn’t perfectly align with every qualification, we encourage you to apply anyway. You may be just the right candidate for this or other roles.