Galaxi Consulting Group
Principal Engineer
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AI Principal Engineer
Role Title
AI Principal Engineer
Client Domain
Banking
Location
London
Duration
6 Months (Extendable)
Hybrid Working
Experience
15 Years
B2B Contract Employment
Job Description
Who we're looking for
We're looking for an experienced Principal Engineer to play a key role in shaping and delivering AI-driven solutions that will serve the entire organization. This is a fast-paced, high-impact role, ideal for engineers who thrive in rapid iteration cycles and want to shape how applied AI delivers real business value across a global enterprise.
As a member of the team, you’ll drive the development of Agentic AI systems, leveraging best of breed LLMs, AI cloud services and frameworks. Your work will help scale AI adoption across the organisation, ensuring solutions are robust, reliable, explainable, and operationally sound.
You should be highly proficient in Python and modern engineering practices, comfortable working across both backend and frontend environments, and experienced in translating traditional software engineering approaches into emerging AI-assisted methods. Strong collaboration, evaluation-driven thinking, and a product mindset are essential.
If you're excited by the challenge of delivering Agentic AI solutions at scale and influencing how AI transforms an enterprise, we’d love to hear from you.
The team
The “AI and Innovation” team is part of the Global Technology division, operating as a centre of excellence for applied AI and agentic systems. We deliver AI-enabled products, frameworks, and internal tools used across the business, helping teams adopt modern AI patterns safely, reliably, and efficiently. We work across the full lifecycle from experimentation to productionisation, using agile and DevOps practices.
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What you'll do
- Design, develop, and deliver AI-enabled features and agent-driven workflows that solve real business challenges.
- Build resilient production systems leveraging cloud-native AI services, agent frameworks, and LLM APIs (e.g., OpenAI, Anthropic).
- Implement agent-based architectures encompassing reasoning loops, guardrails, observability, and operational controls.
- Collaborate closely across teams to gather requirements and iterate quickly, employing agile and DevOps principles.
- Champion quality and security with a “shift-left” testing mindset, ensuring compliance and reliability in AI solutions.
- Monitor AI system behaviour post-deployment, clearly communicating limitations, risks, and performance.
- Use AI-assisted coding tools to boost developer productivity and code quality within the team.
- Engage in continuous improvement through code reviews, evaluation design, and metrics-driven iteration.
The knowledge, experience and qualifications you need
- Strong software engineering background, with Python-first development experience.
- Proven experience building production systems that integrate with LLM API services e.g. OpenAI API services.
- Hands-on experience with agentic or tool-using AI systems, including orchestration, memory, and toolchains.
- Experience designing and using evals to measure model quality, reliability, safety, and regression.
- Comfort working with cloud managed AI services and modern agent frameworks.
- Familiarity with RAG workflows, vector stores, embedding design, and latency/cost trade-offs.
- Experience thinking about (and engineering for) failure modes, guardrails, operational reliability, and user impact.
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The knowledge, experience and qualifications that will help
- You’ve experienced the transition from traditional software engineering to AI-first environments.
- Exposure to AWS Bedrock, Azure Foundry, or similar cloud AI agent platforms.
- Knowledge of interoperability standards (A2A, MCP).
- Experience with containerisation (Docker, Kubernetes) and modern DevOps tooling.
- Active contributor to engineering communities, continuous learning, and knowledge sharing.
What you'll be like
- A curious technologist who stays up-to-date with AI and software trends.
- Someone who values quality, security, and solid engineering practices.
- Collaborative communicator, comfortable working with diverse teams across locations and time zones.
- Resilient and positive, able to manage pressure with professionalism.
- Self-motivated, analytical, and solution-oriented with a growth mindset.
- Demonstrates integrity, fairness, and respect for all colleagues.
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