Machine learning operations architect Work, Jobs in Forest Hill, Gtl (with Salaries)

AI Large Language Mode (LLM) Technology Lead/Principal Architect
Accenture —London
- Full-time
- Master's degree
- Bachelor's degree
- Machine learning
AI Solutions Engineer - Vice President - London
Goldman Sachs —London
- Full-time
- Azure
- Computer Science
- Engineering
- Employee assistance programme
Principal, Lead Engineer AI
European Bank for Reconstruction and Development —London
- Azure
- Computer Science
- English
Lead Software Engineer, VP
State Street —London
- Full-time
- Computer Science
- DevOps
- Engineering
13d
Software Developer, Scaled Ops AI Acceleration Team
Meta —London
- Full-time
- Computer Science
- Engineering
- Data analysis skills
4d
Global Fraud Lead
Cover Genius —London
- Full-time
- Hybrid work
- Machine learning
- Leadership
- Work from home
Senior Specialist Solutions Architect (AI/ML)
Databricks —London
- Azure
- Sales
- Master's degree
Quick apply
Senior Data Platform Engineer
DraftKings —London
- Full-time
- AWS
- Communication skills
- Python
Senior Presales Consultant
Fintech OS SRL —London
- Full-time
- Hybrid work
- Up to 50% travel
- Travel
- APIs
Quick apply
Tech Lead - Data Engineering
Plentific —London
- Hybrid work
- SQL
- Machine learning
- APIs
- Employee assistance programme
- Life insurance
Quick apply
XVA - Lead Software Engineer
Citi —London
- Full-time
- Hybrid work
- Azure
- Computer Science
- PMP
- Annual leave
- Employee assistance programme
Azure DevOps Engineer
UBDS Group —London
- Full-time
- Hybrid work
- Azure
- Linux
- Communication skills
Quick apply
Associate Forward Deployed Engineer (AI)
TP ICAP —London
- Full-time
- AWS
- Machine learning
- APIs
AI Systems Technology Architect | London
Infosys —London
- Azure
- DevOps
- Master's degree
AI - Solutions Architect
10Pearls —London
- Full-time
- Azure
- Doctoral degree
- Computer Science
Principal Google Cloud Architect
Datatonic —London
- Full-time
- Hybrid work
- Azure
- Oracle
- Computer Science
- Life insurance
Cloud Engineering & Architecture - Senior Platform Engineer AI - Vice President
Goldman Sachs —London
- Full-time
- DevOps
- Master's degree
- AWS
- Employee assistance programme
6d
Global Banking & Markets - London - Associate / Vice President - Business Analyst
Goldman Sachs —London
- Full-time
- Computer Science
- AWS
- Bachelor's degree
- Employee assistance programme
13d
Senior Machine Learning Engineer
bp —Sunbury
- Full-time
- Hybrid work
- Doctoral degree
- No experience needed
- Java
- Relocation assistance
12d
Agentic / GenAI Consultant / Senior Consultant
Capgemini Sogeti —London
- Hybrid work
- Azure
- Master's degree
- SQL

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AI Large Language Mode (LLM) Technology Lead/Principal Architect

Accenture -
London

Apply Now

Job details

Full-time

Qualifications

Law
MCP
Big data
Master's degree
Bachelor's degree
Machine learning
Deep learning
Natural language processing
AI
Graph databases

Full job description

AI Large Language Mode (LLM) Technology Lead/Principal Architect

Career Level: Manager / Senior Manager / Associate Director

YOU ARE

As a Lead or Principal AI Architect, you will serve as the definitive technical authority on AI architecture within client engagements and across the practice. You will own the complete, end-to-end architecture of advanced AI platforms and solutions — spanning classical machine learning, generative AI, and agentic systems — ensuring every domain of the architecture is cohesively designed, technically sound, and purposefully aligned to client business objectives and enterprise-grade standards.

A defining dimension of this is your ability to operate at the executive level — working closely with CIOs, CTOs, and senior business leaders to help shape and articulate the enterprise AI strategy. You will connect business goals, priorities, and transformation agendas to a coherent technical vision, ensuring AI investments are purposeful, sequenced, and positioned to deliver lasting competitive advantage. This strategic partnership with client leadership distinguishes you as both a trusted advisor and a principal architect.

In this , you will lead and integrate the work of multiple domain architects and subject matter specialists — across areas such as agentic application design, AI security and trust, AI operations and observability, data and knowledge engineering, and model platforms and inference — providing the architectural vision, technical governance, and cross-domain coherence that binds their contributions into a unified, enterprise-ready system. You will set the architectural direction, resolve cross-domain tensions, and make the critical design decisions that shape the entire AI solution. Beyond client delivery, you will be recognized as a thought leader and leading authority in AI — staying at the forefront of the latest research, emerging standards, industry innovations, and evolving technology landscapes. You will actively shape the practice's AI architecture point of view, contribute to internal knowledge, frameworks, and reusable assets, and represent the firm externally through publications, conference engagements, and client advisory conversations. Your perspective on where AI is heading will be sought by clients, practice leadership, and peers alike.

You will evaluate and make definitive decisions on design patterns, technical frameworks, reference architectures, and technology selections — balancing innovation with pragmatism to deliver systems that are robust, scalable, and built to last. This includes providing architectural oversight across AI agent ecosystems encompassing multi-agent orchestration, tool use, skills use, and memory systems, as well as foundation model integration, fine-tuning strategies, and classical ML model deployment within cohesive, production-ready platforms. You will be accountable for ensuring the complete architecture meets the most rigorous non-functional requirements across security, observability, governance, performance, and scalability — and that these concerns are addressed holistically and consistently across all domains. You will produce and govern the authoritative architecture artifacts that guide delivery at scale — including architecture decision records (ADRs), reference architectures, component and data flow diagrams, and integration specifications — and provide the executive-level technical leadership that gives cross-functional engineering teams, domain architects, and client stakeholders the clarity and confidence to execute. Your work will be instrumental in defining how the most ambitious clients adopt, scale, and lead with AI — setting a standard for what advanced AI architecture can and should look like, and delivering transformational, lasting business value.

THE WORK

Partner with CIOs, CTOs, and business leaders to shape the enterprise AI strategy, connecting business goals to a coherent, sequenced technical vision

Lead enterprise AI assessments and build enterprise AI implementation roadmaps that sequence investments for lasting competitive advantage

Own the complete, end-to-end technical solution for complex AI platforms — ensuring every domain is cohesively designed and aligned to business objectives and enterprise standards

Translate the governing architecture principles into a concrete, defensible technical solution that domain teams build against

Build innovative prototypes and proofs of concept hands-on, using emerging technologies to de-risk decisions and prove value early

Perform technology assessments and comparisons, making definitive, evidence-based recommendations on tools, frameworks, and platforms

Set the architectural direction for model- and tool-agnostic multi-agent ecosystems — orchestration, memory, and tool/skill use — governed through a registry-bound AI Gateway

Establish the agent registry and certification model that mandates no uncertified agent reaches production

Define memory as a first-class abstracted platform service, decoupled from any underlying vendor engine

Define the foundation model and inference strategy — adaptation, fine-tuning, and dynamic cost/quality/latency-aware routing

Set the standards for high-throughput, low-latency inferencing and classical ML deployment within unified, production-ready platforms

Own the architecture of the enterprise context layer — knowledge graphs, ontologies, vector search, and semantic retrieval — grounding the solution in client knowledge

Set the design direction for context assembly and memory that manages prompts, context windows, and conversational state across the platform

Be accountable for security, governance, observability, performance, and scalability addressed holistically and consistently across every domain

Establish the identity and authorization model — per-agent identity, IAM/IAP binding, and defense-in-depth enforcement

Define the layered guardrail framework applied at every boundary, balancing protection with performance

Govern the MCP control plane — registry, gateway, and risk scoring — across all internal and third-party servers

Mandate adopt-over-build for productized evaluation and observability stacks

Establish FinOps as a first-class concern — usage labelling, gateway-enforced budgets, and cost-per-archetype as a planning input

Make the definitive decisions on design patterns, reference architectures, frameworks, and technology selections, balancing innovation with pragmatism

Lead and integrate the work of domain architects and specialists, resolving cross-domain tensions into a unified, enterprise-ready system

Build the practice's reusable reference architectures, frameworks, and assets, with a deliberate adopt-over-build stance

Conduct deep-dive architecture workshops and working sessions with client executives and engineering teams

Produce and govern the authoritative architecture artifacts — blueprints, reference architectures, ADRs, and integration specifications — that guide delivery at scale

Serve as a recognized thought leader in AI, shaping the practice's point of view and representing the firm externally through publications and conference engagements

EDUCATION

Bachelor's Degree or equivalent

REQUIRED SKILLS / EXPERIENCE:

Extensive experience in designing & deploying enterprise grade advanced ai solutions using agentic, generative and classical AI/ML using at least one cloud vendor.

Proven experience in the LLM and Generative AI space.

Well versed in architecting and operationalizing LLM driven application architecture patterns.

Deep experience in engineering, machine learning, deep learning and NLP solutions and applications
Several years of hands on experience as a machine architect in the industry designing big data, machine learning. large scale analytical engineering solutions

Apply Now

Refine Your Search

machine learning operations architect jobs in forest hill, gtl

AI Large Language Mode (LLM) Technology Lead/Principal Architect

AI Solutions Engineer - Vice President - London

Principal, Lead Engineer AI

Lead Software Engineer, VP

Software Developer, Scaled Ops AI Acceleration Team

Global Fraud Lead

Senior Specialist Solutions Architect (AI/ML)

Senior Data Platform Engineer

Senior Presales Consultant

Tech Lead - Data Engineering

XVA - Lead Software Engineer

Azure DevOps Engineer

Associate Forward Deployed Engineer (AI)

AI Systems Technology Architect | London

AI - Solutions Architect

Principal Google Cloud Architect

Cloud Engineering & Architecture - Senior Platform Engineer AI - Vice President

Global Banking & Markets - London - Associate / Vice President - Business Analyst

Senior Machine Learning Engineer

Agentic / GenAI Consultant / Senior Consultant

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