cloud ai engineer

Google

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor's degree in Computer Science or equivalent practical experience.</li>
<li>3 years of experience building machine learning solutions and working with technical customers.</li>
<li>Experience designing cloud enterprise solutions and supporting customer projects to completion.</li>
<li>Experience coding in one or more general purpose languages (e.g., Python, Java, Go, C or C++) including data structures, algorithms, and software design.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Experience working with recommendation engines, data pipelines, or distributed machine learning.</li>
<li>Experience with deep learning frameworks (e.g., TensorFlow, XGBoost).</li>
<li>Understanding of the auxiliary practical concerns in production machine learning systems.</li>
<li>Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce).</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google&rsquo;s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.</p><br>
<p>
As a Cloud AI Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. You will work closely with product management and product engineering to build and constantly drive excellence in our products.<br>
<br>
In this role, you are the Google engineer working with Google's largest and most motivated Cloud customers. Together with the team you will support customer implementation of Google Cloud products through architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.</p><p><br>
Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.</p></div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Be a trusted technical advisor to customers and solve complex machine learning challenges.</li>
<li>Coach customers on the practical challenges in machine learning systems feature extraction and feature definition, data validation, monitoring, and management of features and models.</li>
<li>Work with customers, partners, and Google Product teams to deliver tailored solutions into production.</li>
<li>Create and deliver best practice recommendations, tutorials, blog articles, and sample code.</li>
<li>Travel up to 30% for in-region for meetings, technical reviews, and onsite delivery activities.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

AI Infrastructure Engineer

<div>Must be a British citizen to meet compliance and security clearance requirements.<h3 class="jobSectionHeader"><b>
Minimum qualifications:</b></h3><ul>
<li>Bachelor&rsquo;s degree in Engineering, Computer Science, a related field, or equivalent practical experience.</li>
<li>8 years of experience with software development using Python or similar coding languages.</li>
<li>Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)).</li>
<li>Experience building pipelines for structured and unstructured data using both vector databases and retrieval augmented generation (RAG) like architectures to power enterprise AI solutions.</li>
<li>Experience leading technical discovery sessions with customers.</li>
<li>Active, or the ability to obtain, a Security Check (SC) UK security clearance.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Master&rsquo;s degree or PhD in AI, Computer Science, or a related technical field.</li>
<li>Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google&rsquo;s Agent Development Kit (ADK)) and patterns like ReAct, self-reflection, and hierarchical delegation.</li>
<li>Experience in a post-sales or technical consulting delivery function.</li>
<li>Knowledge of large language model native metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
As an AI Forward Deployed Engineer (FDE) at Google Cloud, you will be the technical engine of our Innovation team, working directly with highly regulated clients to help them transform their operations using advanced AI/ML technologies. You are an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you will function as a &quot;builder-consultant,&quot; moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer&rsquo;s environment.</p><p>
In this role, you will address blocker to production including solving the integration complexities, data readiness issues, and state-management challenges that prevent AI from reaching enterprise-grade maturity. By embedding with strategic accounts, you will serve a dual purpose: providing &quot;white glove&quot; deployment of complex AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud&rsquo;s future product roadmap.</p><br>
Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.</div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Serve as the lead developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol servers) that drive measurable return on investment.</li>
<li>Architect and code the &quot;connective tissue&quot; between Google&rsquo;s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters.</li>
<li>Build high-performance evaluation (Eval) pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.</li>
<li>Identify repeatable field patterns and technical &quot;friction points&quot; in Google&rsquo;s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.</li>
<li>Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Staff Forward Deployed Engineer, Google Cloud Public Sector

<div>Must be a British citizen to meet compliance and security clearance requirements.<h3 class="jobSectionHeader"><b>
Minimum qualifications:</b></h3><ul>
<li>Bachelor&rsquo;s degree in Engineering, Computer Science, a related field, or equivalent practical experience.<br>
</li>
<li>5 years of experience with software development using Python or similar coding languages.</li>
<li>Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., GCP).</li>
<li>Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions.</li>
<li>Experience leading technical discovery sessions with customers.</li>
<li>Active, or the ability to obtain, a Security Check (SC) UK security clearance.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Master&rsquo;s degree or PhD in AI, Computer Science, or a related technical field.</li>
<li>Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).<br>
</li>
<li>Experience in a post-sales or technical consulting delivery function.</li>
<li>Knowledge of LLM-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
As an AI Forward Deployed Engineer (FDE) at Google Cloud, you will be the technical engine of our Innovation team, working directly with highly regulated clients to help them transform their operations using advanced AI/ML technologies.
</p><p>You will be an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you will function as a builder-consultant, moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer&rsquo;s environment.</p><p>
This role is designed for high-agency engineers with a founder&rsquo;s mindset. You will manage blocker to production including solving the integration complexities, data readiness issues, and state-management challenges that prevent AI from reaching enterprise-grade maturity. By embedding with strategic accounts, you will serve a dual purpose: providing white glove deployment of complex AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud&rsquo;s future product roadmap.</p><p>
Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.</p></div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Serve as the lead developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI).</li>
<li>Architect and code the connective tissue between Google&rsquo;s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters.</li>
<li>Build high-performance evaluation (Eval) pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.</li>
<li>Identify repeatable field patterns and technical friction points in Google&rsquo;s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.</li>
<li>Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Senior Forward Deployed Engineer, Google Cloud Public Sector

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience.</li>
<li>5 years of experience with data structures and algorithms in Python.</li>
<li>3 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.</li>
<li>3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).</li>
<li>Experience with data analysis, data optimizations and data evaluations.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Master's degree or PhD in Computer Science or a related technical field.</li>
<li>5 years of experience working in a complex, matrixed organization.</li>
<li>Experience in Gen AI.</li>
<li>Experience in data optimization and data platforms.</li>
<li>Experience with research to production.</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.</p>
<p>
In this role, you will be a part a team operating in the Gemini Era, where AI is profoundly data-centric, the &ldquo;quality&rdquo; data used for training, fine-tuning, or Retrieval-Augmented Generation (RAG) has greater impact one end product performance than almost anything else.<br>
<br>
Your mission is to improve the time to model quality for users, achieved by bringing data optimization techniques to a broad audience through integrated tools and platforms. In this role, the tooling automatically and efficiently applies data optimization techniques, and runs structured ablations to demonstrate to users which ones work best for their use case, and deliver insights on how to improve further. You will collaborate with key product teams across Google.</p><p><br>
The ML, Systems, &amp; Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
</p><p>We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud&rsquo;s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.</p></div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Scale data optimization techniques (including those from Google Research) to enhance the performance and quality of ML models, while heavily shaping the technical direction of data platforms for model tuning across multiple product areas.</li>
<li>Establish technical relationships with multiple product areas to define strategy and drive technical directions.</li>
<li>Leverage existing assets and techniques from Google Research to accelerate model tuning velocity for teams like Bard and other product areas fine-tuning Gemini models.</li>
<li>Collaborate with Research teams and ML practitioners to identify, build and iterate on engineering tools, processing pipelines, data optimization techniques, integration with existing workflows, user interfaces and supporting users adoption.</li>
<li>Apply research and enage directly with users to advance Google&rsquo;s goal of making AI helpful for everyone.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

AI/ML Senior Software Engineer, Data Optimization and Platform

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience.</li>
<li>2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.</li>
<li>1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).</li>
<li>Experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).</li>
<li>Ability to communicate in French and German fluently to support client relationship management in this region.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Master&rsquo;s degree or PhD in AI, Computer Science, or a related technical field.</li>
<li>Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google&rsquo;s Agent Development Kit (ADK)) and complex patterns like ReAct, self-reflection, and hierarchical delegation.</li>
<li>Knowledge of &quot;LLM-native&quot; metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.</li>
<li>Ability to implement secure agentic workflows incorporating MCP, tool-calling, and OAuth-based authentication.</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2>
Google Cloud&rsquo;s mission is to make every business successful through AI by combining cutting-edge technology, infrastructure, and talent. AI/ML software engineers in Cloud bridge the gap between pioneering models and a massive product vehicle reaching billions. Our talent density and AI-powered tools drive rapid development, rooted in a culture of empowerment and a bias to action. In this role, you aren&rsquo;t just building technology; you&rsquo;re shaping the frontier of enterprise and driving the evolution of advanced models. It's an exciting time to join Google Cloud&rsquo;s Go-To-Market team, leading the AI revolution for businesses worldwide. You&rsquo;ll excel by leveraging Google's brand credibility&mdash;a legacy built on inventing foundational technologies and proven at scale. We&rsquo;ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We&rsquo;re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era&mdash;the market is yours.</div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Serve as the lead developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol (MCP) servers) that drive measurable return on investment.</li>
<li>Architect and code the &quot;connective tissue&quot; between Google&rsquo;s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters.</li>
<li>Build high-performance evaluation (Eval) pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.</li>
<li>Identify repeatable field patterns and technical &quot;friction points&quot; in Google&rsquo;s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.</li>
<li>Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Partner Forward Deployed Engineer III, Generative AI (French, German)

HCLTech

City Of London, England
<br>Job Summary
<br><br>
<b>Job Title:</b> Physical AI Engineer (Robotics & Agentic Systems)
<br>We are looking for an engineer to build the Physical AI solutions using Robotics and edge devices on Google stack. You will integrate Deepmind Robotics model with Gemini 3 foundation models to create autonomous agents that perceive, reason, and act in dynamic industrial environments. Your work will involve moving Physical AI from simulation (MuJoCo-Warp) to production-grade hardware at scale.
<br><br>
Key Responsibilities
<br><br>
Key Responsibilities
<br><ul>
<li>Model Integration: Deploy Gemini Robotics-ER (Embodied Reasoning) models to enable robots to understand natural language instructions and physical causality.</li>
<li>Workflow Orchestration: Utilize the Gemini Enterprise Agent Platform to build agentic workflows that connect cloud-based reasoning with edge-based execution.</li>
<li>Simulation & Training: Use MuJoCo-Warp and G4 VMs (NVIDIA Blackwell) to run high-fidelity simulations, generating synthetic data to train robots on complex edge cases.</li>
<li>Hardware Abstraction: Work within Intrinsic Flowstate to develop hardware-agnostic "Skills" (robotic behaviors) that can be deployed across various robotic arms and sensors (Universal Robots, Foxconn, etc.).</li>
<li>System Optimization: Implement the JAX AI Stack (JAX, Flax, Optax) for efficient, accelerator-oriented computation on Google TPUs and NVIDIA GPUs.</li>
</ul>
Skill Requirements
<br><br>
Technical Requirements
<br>Category Stack Components
<br>Foundation Models Gemini 1.5/3.0, RT-2 (Robotics Transformer), Gemini Robotics-ER
<br>Software Platform Intrinsic Flowstate, ROS 2 (Robot Operating System), Python
<br>Compute & Infra Google Cloud Vertex AI, Google Distributed Cloud (Edge), TPUs
<br>Physics Engines MuJoCo-Warp, NVIDIA Isaac Sim integration
<br>Data & ML JAX, XLA (Accelerated Linear Algebra), Orbax (Checkpointing)
<br><br>
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Principal Engineer

<div>
 Senior Python Engineer &ndash; AI &amp; Intelligent Systems Location London (Hybrid)
 <br/>
 <br/>
 The Opportunity Our client is seeking an experienced Senior Python Engineer to help build the next generation of AI-enabled products and platforms within a highly complex, data-rich environment.
 <br/>
 <br/>
 This role sits within a growing innovation-focused engineering team responsible for developing intelligent systems that improve business processes, automate knowledge work, and unlock new opportunities through applied AI. The successful candidate will contribute directly to the development, deployment, and enhancement of production-grade AI solutions while working alongside experienced engineers, AI specialists, and business stakeholders.
 <br/>
 <br/>
 This is an excellent opportunity for someone who enjoys building products from the ground up, solving complex technical challenges, and working with modern AI technologies in a collaborative environment.
 <br/>
 <br/>
 What You'll Be Doing
 <ul>
  <li>
   Develop and maintain AI-powered products, services, and internal platforms.
  </li>
  <li>
   Build production-ready applications using Python and modern cloud technologies.
  </li>
  <li>
   Develop integrations with LLMs, AI services, and external APIs.
  </li>
  <li>
   Create scalable backend services and data processing pipelines.
  </li>
  <li>
   Work closely with engineers, product teams, and business stakeholders to deliver high-quality solutions.
  </li>
  <li>
   Contribute to the implementation of AI-driven workflows and intelligent automation capabilities.
  </li>
  <li>
   Support the deployment, monitoring, and continuous improvement of AI applications in production.
  </li>
  <li>
   Write clean, maintainable, and well-tested code following engineering best practices.
  </li>
  <li>
   Explore emerging AI technologies and contribute ideas for future product development.
  </li>
 </ul>
 The role is primarily hands-on engineering, focused on building and delivering software solutions.
 <br/>
 <br/>
 Technology Environment The team works with a modern engineering and AI stack including:
 <br/>
 <br/>
 <ul>
  <li>
   Python
  </li>
  <li>
   OpenAI and LLM technologies
  </li>
  <li>
   Cloud-native platforms
  </li>
  <li>
   Serverless architectures
  </li>
  <li>
   Vector databases
  </li>
  <li>
   Knowledge repositories
  </li>
  <li>
   Modern data engineering tooling
  </li>
  <li>
   AI-enabled development tools and workflows
  </li>
 </ul>
 What We're Looking For Essential Experience
 <ul>
  <li>
   Strong software engineering background with advanced Python development skills.
  </li>
  <li>
   Experience building and deploying cloud-based applications.
  </li>
  <li>
   Experience developing and delivering production-quality software.
  </li>
  <li>
   Experience working with APIs, backend services, and data pipelines.
  </li>
  <li>
   Strong understanding of software engineering best practices, testing, and maintainability.
  </li>
  <li>
   Ability to work effectively within cross-functional teams.
  </li>
  <li>
   Strong problem-solving skills and attention to detail.
  </li>
 </ul>
 Highly Desirable
 <ul>
  <li>
   Experience working with OpenAI APIs and LLM-based applications.
  </li>
  <li>
   Experience building AI-powered products or intelligent user interfaces.
  </li>
  <li>
   Experience with Retrieval-Augmented Generation (RAG) architectures.
  </li>
  <li>
   Understanding of AI agents and agentic workflows.
  </li>
  <li>
   Experience working with vector databases and semantic search technologies.
  </li>
  <li>
   Exposure to data engineering and machine learning workflows.
  </li>
  <li>
   Experience taking AI solutions from proof-of-concept through to production.
  </li>
  <li>
   Experience developing search, knowledge management, or information retrieval platforms.
  </li>
 </ul>
 About You You are a highly capable engineer who enjoys building practical solutions to complex problems. You have a strong foundation in software engineering and are excited by the opportunity to work with modern AI technologies and large-scale data systems.
 <br/>
 <br/>
 You thrive in collaborative environments, enjoy learning new technologies, and take pride in delivering high-quality software that creates meaningful business impact.
 <br/>
 <br/>
 This role offers the opportunity to work on innovative AI initiatives while remaining deeply involved in hands-on engineering and product development.
 <br/>
 <br/>
 <br/>
 <em>
  We believe in equal opportunity for all and actively encourage applications from diverse backgrounds, experiences, and perspectives.
  <br/>
  <strong>
   Source Group International Ltd is acting as an Employment Business in relation to this vacancy&nbsp;
   <br/>
  </strong>
 </em>
</div>


Senior Python Engineer

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