senior technical support engineer

HOMETRACK

<div><p>Hybrid working pattern - 2 days per week from London Bridge Office</p><p>
Hometrack is seeking an experienced Senior Data Engineer to join our product team to help us deliver Hometrack's Data Services ambitions. By building the best property data sets available, which back the market leading AVM, trusted by 17 out of the top 20 mortgage lenders in the UK, we open the door to helping all our customers make the decisions that matter to them - to buy, to lend, to build.</p><p></p><p>
The Data Services team works with 100s of customers across the property sector ranging from mortgage lenders, house builders, investors, fin &amp; proptech, insurers, telco, retail and utilities, as well as others involved in the housing market. Our mission is to inform decision makers by putting the UK&rsquo;s most trusted property data and insights at the heart of the property ecosystem.</p><p></p><p>
Our market intelligence and customer acquisition, retention and engagement solutions are relied upon by leading industry professionals.</p><p></p><p>
Data Services has a diverse product range covering market, property and mover intelligence, delivered through varying mechanisms including data platforms, reports and APIs, providing maximum flexibility when matching our customers&rsquo; needs to the most effective data solution.</p><p></p><p>
Hometrack is looking for an experienced senior data engineer to help us make this a reality.</p><p>
What we&rsquo;re looking for in a Senior Data Engineer:</p><ul><li>
Be accountable for team outcomes, playing your part in achieving team goals and ensuring your contribution positively impacts overall success</li><li>
Be a continual improver, looking for ways to help the team do better and be better, again and again</li><li>
Write maintainable, testable code and enjoy providing code reviews</li><li>
Be experienced with Databricks, Delta Lake and Lakehouse architecture for efficient data management; experience with ETL processes and optimizing data pipelines for performance</li><li>
Be strong in Python, SQL, and PySpark</li><li>
Be passionate about building data products for stakeholders and customers, ensuring they are stable, scalable, secure, accurate, observable, and performant</li><li>
Enjoy collaborating closely with colleagues in Product, Analytics, Security, and Software, explaining technical concepts to non-technical audiences</li></ul></div>

Senior Data Engineer

Cushman & Wakefield

<div><p><b>Job Title</b></p>
Junior Analytics Engineer<p><b>
Job Description Summary</b></p><p><b>
Job Description</b></p><p>
As a Junior Analytics Engineer within the EMEA Business Intelligence team, you will be an integral part of the Analytics Engineering pillar, contributing to the development and maintenance of the data foundation that powers BI delivery across EMEA. Working closely with senior Analytics Engineers, you will support the design and build of semantic models, curated datasets, and reusable data assets on our central data platform, gaining hands-on experience with enterprise-scale data modelling and platform engineering in a collaborative, high-performing team. You will work in close collaboration with the BI and Data Science &amp; Engineering teams, helping to lay the groundwork for data assets that increasingly support AI and agentic use cases alongside traditional BI delivery. You will start to develop an understanding of the business context behind the data you work with, helping to translate business needs into well-structured data assets and beginning to build the analytics translation skills that connect data and business outcomes. This is a role for someone who is technically curious, eager to learn, and motivated to build a strong foundation in analytics engineering. You will be guided and supported throughout, with clear opportunities to grow your skills, take on increasing responsibility, and develop toward a more senior role within the pillar.</p><p></p><p><b>
Responsibilities:</b></p><ul><li><p>
Contribute to the design, build, and maintenance of semantic models and curated datasets on our central data platform, working under the guidance of senior Analytics Engineers.</p></li><li><p>
Support the standardisation of datasets, business logic, and data models to enable reusability and consistency across BI teams and markets.</p></li><li><p>
Assist with onboarding market-specific datasets onto our central data platform, collaborating with local stakeholders to understand data sources and requirements.</p></li><li><p>
Work closely with senior team members to ensure data assets meet the requirements of BI products being developed by the BI Development team.</p></li><li><p>
Develop a working understanding of the business context behind data requests, supporting senior team members in translating business needs into data structures and logic.</p></li><li><p>
Collaborate closely with Data Science &amp; Engineering colleagues, building familiarity with how data assets are used and shared across teams.</p></li><li><p>
Contribute to data quality checks and basic performance monitoring of data models and semantic layers, supporting senior team members in identifying improvements.</p></li><li><p>
Support early-stage work on building data foundations that can be used for AI and agentic use cases, such as preparing clean, well-structured datasets ready for future AI applications.</p></li><li><p>
Maintain clear documentation of data models, datasets, and platform assets, ensuring work is well-described and easy for others to understand and build on.</p></li><li><p>
Participate in peer reviews of data models and platform assets, incorporating feedback constructively to develop technical skills and maintain quality standards.</p></li><li><p>
Follow established best practices for data modelling, naming conventions, and platform governance, developing familiarity with the team's standards and ways of working.</p></li><li><p>
Engage actively in training, bootcamps, and mentoring programmes, taking ownership of personal development and building expertise in the tools and technologies used by the team.</p></li><li><p>
Support testing and quality assurance activities across project delivery, helping to ensure data assets and platform changes are reliable before release.</p></li></ul><p></p><p><b>
Requirements:</b></p><ul><li><p>
Bachelor's or Master's degree in Computer Science, Data Engineering, Mathematics, Statistics, or a related technical discipline.</p></li><li><p>
Some practical experience with data engineering, analytics engineering, or BI development through employment, internships, or academic projects.</p></li><li><p>
Foundational understanding of SQL and a willingness to develop proficiency in building and optimising data models.</p></li><li><p>
Basic familiarity with data modelling concepts such as star schema or dimensional modelling; formal experience is an advantage but not required.</p></li><li><p>
Exposure to enterprise data platforms such as Databricks, Microsoft Fabric, Azure Synapse, or Snowflake is desirable.</p></li><li><p>
Awareness of Power BI or other BI tools and an interest in understanding how data assets underpin BI product development.</p></li><li><p>
Curiosity about AI, machine learning, and agentic technologies, and how data platforms are structured to support these use cases.</p></li><li><p>
An interest in understanding business needs and translating them into data and analytics solutions, with a willingness to develop commercial awareness alongside technical skills.</p></li><li><p>
Strong attention to detail and a methodical approach to building, testing, and documenting data assets.</p></li><li><p>
A collaborative and proactive mindset, with the eagerness to learn from senior team members and contribute to a high-performing team.</p></li><li><p>
Good communication skills, with the ability to ask clear questions and document work clearly.</p></li><li><p>
Knowledge of the real estate sector is a plus but not required.</p></li><li><p>
Fluent in English; additional European languages are an advantage.</p></li></ul><p></p><p><br>
Cushman &amp; Wakefield is an equal opportunity / affirmative action employer. All qualified candidates will receive consideration for employment without regard to ethnicity, gender, gender identity or expression, sexual orientation, age, disability, religion, marital status, or any other legally protected characteristic. Cushman &amp; Wakefield is committed to equity in employment, and our goal is to have a diverse, inclusive and barrier-free workplace. If you are a person with a disability and need any other accessible accommodations during the hiring process, you are invited to bring this to the Talent Acquisition Advisor&rsquo;s attention once they have made contact.</p><br>
<p></p>
INCO: &ldquo;Cushman &amp; Wakefield&rdquo;</div>

Junior Analytics Engineer

Worldpay

<div><p><b>Ready to take your career global?</b></p><p>
Make your mark at one of the biggest names in payments.</p><p>
We are seeking an experienced <b>Senior ML Software Engineer</b> to join our Data Science Enablement team. You will be the primary software engineering expert for a product area, working as part of a cross-functional agile team and owning the successful launches and ongoing operations of high-profile products in production. Your focus will be on driving new feature delivery, maintaining operational excellence, and collaborating on enhancements to our shared ML platform. You will work closely with cross-functional collaborators&mdash;including ML research engineers, product managers, and platform engineers&mdash;to deliver scalable, reliable, and low-latency ML solutions.</p><p>
In addition to technical expertise, this job requires strong collaboration skills.</p><p></p><p><b>
What you&rsquo;ll own</b></p><p>
Feature Development &amp; Delivery:</p><ul><li>
Design, implement, and deploy new features and enhancements to ML products, collaborating with Product and ML Research teams to refine requirements.</li></ul><p>
Technical Ownership and Stewardship:</p><ul><li>
Technical ownership of existing and new production ML products in your area, ensuring alignment of technical investments with business goals (in collaboration with a product owner) and engineering best practices.</li><li>
End-to-end technical stewardship of ML products, ensuring ongoing reliability and performance.</li></ul><p>
Contribute to ML platform:</p><ul><li>
Contribute to the evolution of the shared ML platform alongside other engineers to drive best practices and shared tooling across all products.</li></ul><p>
Operational Excellence:</p><ul><li>
Maintain and improve automated CI/CD pipelines, testing frameworks, and monitoring/logging, ensuring high operational standards.</li><li>
Conduct comprehensive code reviews to enforce coding standards, improve code quality, and share knowledge.</li></ul><p>
Continuous Improvement:</p><ul><li>
Identify and implement opportunities for process, tooling, and system improvements, proactively addressing technical debt and scaling challenges.</li></ul><p>
Release Management:</p><ul><li>
Oversee pre-release testing, coordinate releases and ensure smooth enablement of new features.</li></ul><p>
Leadership:</p><ul><li>
Provide technical guidance and support to other engineers and data scientists to solve complex technical challenges.</li><li>
Mentor and coach other engineers, supporting their professional growth.</li><li>
Foster a culture of collaboration, continuous improvement, and knowledge sharing.</li></ul><p>
Act Like an Owner:</p><ul><li>
Proactively identify and resolve blockers, navigate processes, and independently seek out information and connect with relevant teams to drive solutions in the face of ambiguity.</li><li>
Operate with a strong sense of urgency, consistently prioritizing and executing tasks to meet timelines and deliver results.</li></ul><p></p><p><b>
What you&rsquo;ll bring</b></p><ul><li>
5+ years as an ML-focused software engineer, ML Engineer, MLOps Engineer, or similar, with hands-on production experience</li><li>
Proven expertise with ML model deployment, API design, and integration into production environments</li><li>
Strong Python programming and relevant ML/data libraries</li><li>
Experience with containerization, orchestration, and AWS cloud services</li><li>
Building and operating CI/CD pipelines</li><li>
Monitoring, troubleshooting, and optimizing production ML systems</li><li>
Pre-release testing and release management</li><li>
Demonstrated ability to work independently, navigate ambiguity, and deliver results</li><li>
Excellent communication skills and ability to collaborate both within engineering organizations and on cross-functional teams</li><li>
Experience with OpenAPI, FastAPI, or similar</li></ul><p></p><p><b>
It&rsquo;s a bonus if you have</b></p><ul><li>
Experience with MLFlow, model versioning, and storage</li><li>
Familiarity with Databricks or similar platforms</li><li>
Experience supporting high-volume, real-time data products</li><li>
Automated testing and validation frameworks</li><li>
Experience designing and configuring low-latency databases to serve real-time features, such as DynamoDB</li><li>
Experience with Terraform Cloud</li><li>
Experience in large companies, mature engineering teams, and/or highly regulated industries</li><li>
AI-assisted coding experience (e.g. GitHub Copilot)</li></ul><p></p><p><b>
Why Join Us?</b></p><ul><li>
Impact: Play a key role as the technical owner of high-profile ML products delivering meaningful business impact to merchants and advancing key pillars of the company&rsquo;s strategy. Your work will directly influence the reliability, scalability, and evolution of critical production systems.</li><li>
Autonomy: Take end-to-end technical ownership of your product area, with the freedom and responsibility to drive technical solutions, shape best practices, and deliver results in a fast-paced, supportive environment.</li><li>
Collaboration: Join a cross-functional, high-performing team where your expertise is valued and your contributions make a real difference.</li></ul><p></p><p><b>
About the team</b></p><p>
Our inclusive and global teams win together every day. We&rsquo;re proud to have the best minds in the industry, whom you can learn from as you grow your career. The people, the energy, and the connections are unmatched. Come and be part of an ever-evolving company and get dynamic opportunities that transcend borders.</p><p></p><p><b>
What makes a Globalpayer?</b></p><p>
Globalpayers think like a client, act like an owner, and win as one team. We&rsquo;re curious and innovative &ndash; always finding better ways to deliver impact. We empower each other to make decisions, and our passion drives excellence in everything we set out to do.</p><p></p><p>
Does this sound like you? Then you sound like a Globalpayer. Apply now to take your career global.</p><p></p><p>
#LI-AB1</p></div>

Senior ML Software Engineer

Bloomberg

<div>
 Location
 <br/>
 <br/>
 London
 <br/>
 <br/>
 Business Area
 <br/>
 <br/>
 Engineering and CTO
 <br/>
 <br/>
 Ref #
 <br/>
 <br/>
 10049302
 <br/>
 <br/>
 <strong>
  Description &amp; Requirements
  <br/>
  <br/>
 </strong>
 Bloomberg&rsquo;s Engineering AI department has 400+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products. At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.
 <br/>
 <br/>
 Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions.
 <br/>
 <br/>
 Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.
 <br/>
 <br/>
 We are looking for Senior ML Platform Engineers with strong expertise and passion for building platforms for (Gen) AI applications.
 <br/>
 <br/>
 As a Senior ML Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed AI development life cycle to enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as, Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud-native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source.
 <br/>
 <br/>
 <strong>
  Join the AI Group as a Senior ML Platform Engineer and you will have the opportunity to:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Architect, build, and diagnose multi-tenant AI platform systems
  </li>
  <li>
   Work closely with AI application teams to design seamless workflows for continuous model training, inference, and monitoring
  </li>
  <li>
   Work with AI experts to understand workflows, pinpoint, and resolve inefficiencies, and to inform the next set of features for the platforms
  </li>
  <li>
   Collaborate with open-source communities and AI application teams to build a cohesive MLOps experience
  </li>
  <li>
   Design CI/CD automation frameworks that incorporate regulatory requirements
  </li>
  <li>
   Develop cloud-native deployment patterns for AI systems across environments
  </li>
  <li>
   Troubleshoot and debug user issues
  </li>
  <li>
   Provide operational and user-facing documentation
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  We are looking for a Senior ML Platform Engineer with:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Proven years of experience working with an object-oriented programming language (Python, Go, etc.)
  </li>
  <li>
   Experience designing cloud-native, distributed platforms
  </li>
  <li>
   Strong knowledge of Kubernetes, Argo, and container orchestration technologies
  </li>
  <li>
   Previous experience with modern CI/CD tools and GitOps workflows
  </li>
  <li>
   Familiarity with implementing automation for model development lifecycles
  </li>
  <li>
   A proactive mentality and ability to collaborate with peers, stakeholders, and management
  </li>
  <li>
   A Degree in Computer Science, Engineering, Mathematics, or similar field of study or equivalent work experience
  </li>
  <li>
   An understanding of Computer Science fundamentals such as data structures and algorithms
   <br/>
   <br/>
  </li>
 </ul>
 We give back to the technology community and you can read more about our outreach at:
 <br/>
 <br/>
 If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
 <br/>
 <br/>
 Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.
</div>


Senior ML Platform Engineer - Artificial Intelligence

Ciklum

<p></p><div><div><div><div><div><div><div><div><div><div><div><b>Ciklum</b> is looking for a <b>Expert Agentic AI Engineer</b> to join our team full-time in the UK .<br>
We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live.</div><p><b>
About the role:</b></p><p>
As a Expert Agentic AI Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.</p><p><b>
Responsibilities:</b></p><ul><li>
Design, build, train, and deploy production-grade Machine Learning, Deep Learning, or Natural Language Processing (NLP) models</li><li>
Optimize ML models for enterprise-scale latency, throughput, and performance, ensuring flawless integration with data warehouses and automated workflow bots</li><li>
Partner with Data Engineers to engineer high-quality data pipelines, automated feature stores, and secure data preprocessing routines</li><li>
Establish and scale MLOps workflows to handle model lineage tracking, code versioning, automated validation gates, and continuous deployment pipelines</li><li>
Set the core technical direction for AI engineering across squads, evaluate emerging AI methodologies, and provide high-level mentorship to senior team members</li></ul><p><b>
Requirements:</b></p><ul><li>
5+ years (Senior) or 8+ years (Expert) of professional experience developing, shipping, and maintaining machine learning models in live production environments</li><li>
Agentic Frameworks: Hands-on experience building autonomous workflows, custom plugins, and orchestration logic using Microsoft Copilot Studio or semantic kernels</li><li>
Cloud AI Infrastructure: Proven experience deploying and fine-tuning generative AI models, prompt flow, and vector databases within Azure AI Foundry (formerly Azure AI Studio)</li><li>
Tool Integration: Strong background in connecting LLMs to external APIs, enterprise data sources, and robotic process automation (RPA) tools to enable autonomous action execution</li><li>
Elite proficiency in Python paired with extensive experience using core ML libraries and frameworks (such as PyTorch, TensorFlow, Scikit-Learn, or Hugging Face)</li><li>
Hands-on experience working with MLOps tracking tools and cloud-based AI infrastructure ecosystems (such as MLflow, Kubeflow, AWS SageMaker, or Azure ML)</li><li>
Strong computer science fundamentals, including advanced knowledge of data structures, algorithmic complexity, and clean code principles. a formal degree in Computer Science, Data Science, Mathematics, or a highly quantitative field is strongly preferred</li></ul><p><b>
What`s in it for you?</b></p><ul><li>
Strong community: Work alongside top professionals in a friendly, open-door environment</li><li>
Growth focus: Take on large-scale projects with a global impact and expand your expertise</li><li>
Tailored learning: Boost your skills with internal events (meetups, conferences, workshops), Udemy access, language courses, and company-paid certifications</li><li>
Endless opportunities: Explore diverse domains through internal mobility, finding the best fit to gain hands-on experience with cutting-edge technologies</li><li>
Care: Healthcare, Basic Life Insurance, Short and Long-term disability insurance according to the Company&rsquo;s Benefit Plans</li></ul><p><b>
About us:</b></p><p>
At Ciklum, we are always exploring innovations, empowering each other to achieve more, and engineering solutions that matter. With us, you&rsquo;ll work with cutting-edge technologies, contribute to impactful projects, and be part of a One Team culture that values collaboration and progress. In the UK, Ciklum is growing fast&mdash;inviting experienced professionals to lead digital transformation alongside Fortune 500 clients. Be part of a company where innovation and impact go hand in hand.</p><p><b>
Explore, empower, engineer with Ciklum!</b></p><p>
Interested already? We would love to get to know you! Submit your application. We can&rsquo;t wait to see you at Ciklum.</p><p>
#LI-VH1</p></div>
</div></div></div></div></div></div><div></div><div><div><div><div><div><div><p>REQUIRED SKILLS</p>
<div><ul><p>Agentic AI</p>
</ul></div></div></div></div></div></div></div><div></div><div><div><div><div><div><div><div>
</div></div></div></div></div></div></div><div><div><div><div><div><div><p>JOB INFO</p>
<div><div><div><ul><div><div>Job Identification</div>
<div>3619</div>
</div><div><div>Job Category</div>
<div>Intelligent Automation</div>
</div><div><div>Posting Date</div>
<div>07/03/2026, 02:34 AM</div>
</div><div><div>Locations</div>
<div> <div></div><div><div>London
</div></div>(Hybrid)</div></div></ul></div></div></div></div></div></div></div></div></div></div></div></div><p></p>

Expert Agentic AI Engineer

Commerce

<div><h1 class="jobSectionHeader"><b>Welcome to the Agentic Commerce Era
</b></h1><p></p><p>At Commerce, our mission is to empower businesses to innovate, grow, and thrive with our open, AI-driven commerce ecosystem. As the parent company of BigCommerce , Feedonomics , and Makeswift , we connect the tools and systems that power growth, enabling businesses to unlock the full potential of their data, deliver seamless and personalized experiences across every channel, and adapt swiftly to an ever-changing market. We believe in harnessing AI responsibly to unlock new possibilities, and we&rsquo;re looking for individuals who use it intentionally to solve problems, accelerate outcomes, and expand what&rsquo;s possible in their role. Our purpose is to help businesses confidently solve complex commerce challenges so they can build smarter, adapt faster, and grow on their own terms. If you want to be part of a team of bold builders, sharp thinkers, and technical trailblazers who shape the future of commerce, this is the place for you.
</p><p></p><h1 class="jobSectionHeader"><b>Senior Software Engineer - Data Team
</b></h1><p>Location: London / UK (Hybrid)
</p><p>Company: Commerce<br>
</p><br>
<h2 class="jobSectionHeader"><b>About Commerce
</b></h2><p>Commerce is an open SaaS ecommerce platform that helps merchants build, run, and grow their businesses.
</p><p>The Data Team builds systems that support merchant-facing products, integrations, analytics, reporting, and the infrastructure behind them.<br>
</p><br>
<h2 class="jobSectionHeader"><b>About The Role
</b></h2><p>We are looking for a Senior Software Engineer who can own complex problems from discovery through production.
</p><p>This role is not narrowly frontend, backend, or data engineering. The right person can work across services, APIs, event flows, product experience, production debugging, and cross-team delivery.
</p><p>They should be comfortable taking an unclear business or customer problem, breaking it down, making trade-offs clear, and shipping a reliable solution.
</p><p>We need someone who raises the engineering bar without needing a lot of direction.<br>
</p><br>
<h2 class="jobSectionHeader"><b>What You Will Do
</b></h2><ul><li>Design and build reliable services, APIs, and product-facing workflows.
</li><li>Work across backend systems, UI surfaces, event processing, and third-party integrations.
</li><li>Turn unclear problems into concrete technical plans.
</li><li>Own production behavior, including monitoring, alerting, logging, debugging, and runbooks.
</li><li>Work with product, design, infrastructure, support, and other engineering teams.
</li><li>Improve quality through tests, code review, observability, and simpler designs.
</li><li>Use data and production evidence to validate decisions.
</li>Take ownership of incidents and production issues when systems do not behave as expected.<br>
<li>
</li></ul><br>
<h2 class="jobSectionHeader"><b>What We Are Looking For
</b></h2><ul><li>Strong senior-level engineering judgment.
</li><li>Experience owning ambiguous technical work.
</li><li>Ability to solve problems across multiple layers of a system.
</li><li>Strong backend engineering experience with production services.
</li><li>Enough frontend experience to work on product-facing workflows when needed.
</li><li>Comfort with distributed systems, event-driven flows, caching, retries, rate limits, and failure modes.
</li><li>Strong production debugging skills.
</li><li>Ability to explain trade-offs clearly.
</li><li>Bias toward simple, reliable solutions.
</li>Good communication during incidents, reviews, and cross-team work.<br>
<li>
</li></ul><br>
<h2 class="jobSectionHeader"><b>Technical Experience
</b></h2><ul><li>5+ years of software engineering experience.
</li><li>Strong experience with Java, Scala, Kotlin, Go, or a similar backend language.
</li><li>Experience building APIs, services, and integrations.
</li><li>Experience with SQL and data-backed product behavior.
</li><li>Experience with GCP, AWS, or another cloud platform.
</li><li>Experience with Kafka, RabbitMQ, Pub/Sub, or similar event systems.
</li><li>Experience with logs, metrics, dashboards, alerts, and tracing.
</li>Experience writing automated tests and reviewing code.<br>
<li>
</li></ul><br>
<h2 class="jobSectionHeader"><b>Useful Experience
</b></h2><ul><li>React / TypeScript or similar frontend experience.
</li><li>Experience with merchant-facing or customer-facing product workflows.
</li><li>Experience with third-party integrations, account linking, OAuth, or external APIs.
</li><li>Experience with Redis, caching, rate limiting, queues, or high-volume event processing.
</li>Experience with analytics, reporting, attribution, or event data products.<br>
<li>
</li></ul><br>
<h2 class="jobSectionHeader"><b>Mindset
</b></h2><ul><li>Own the outcome, not only the ticket.
</li><li>Ask what problem we are solving before choosing the implementation.
</li><li>Prefer simple designs that other engineers can operate.
</li><li>Validate risky assumptions early.
</li><li>Use production data and customer impact to guide decisions.
</li><li>Escalate early when risk, ownership, or scope is unclear.
</li>Do not take shortcuts around process, security, or production safety.<br>
<li>
</li></ul><br>
<h2 class="jobSectionHeader"><b>What Good Looks Like
</b></h2><p>A strong candidate can describe systems they owned, incidents they handled, trade-offs they made, and mistakes they learned from.
</p><p>They should be able to explain how they approach unclear problems, reduce risk before production, and make systems easier for the team to operate.
</p><p>They should not need a tech lead to turn every ambiguous problem into a detailed task list.
</p><p></p><h1 class="jobSectionHeader"><b>Inclusion and Belonging
</b></h1><p></p><p>At Commerce, we believe that celebrating the unique histories, perspectives and abilities of every employee makes a difference for our company, our customers and our community. We are an equal opportunity employer and the inclusive atmosphere we build together will make room for every person to contribute, grow and thrive.
</p><p></p><p>We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the interview process, to perform essential job functions and to receive other benefits and privileges of employment. If you need an accommodation in order to interview at Commerce, please let us know during any of your interactions with our recruiting team.
</p><p></p><p>Learn more about the Commerce team, culture and benefits at https://www.commerce.com/careers/
</p><p></p><h1 class="jobSectionHeader"><b>Protect Yourself Against Hiring Scams: Our Corporate Disclaimer
</b></h1><p></p><p>Commerce, along with many other employers, has become the subject of fraudulent job offers to hopeful prospective job seekers.
<br>
<br>
Be advised:
<br>
Commerce does not offer jobs to individuals who do not go through our formal hiring process.
<br>
<br>
Commerce will never:
</p><ul><li><p>require payment of recruitment fees from candidates;
</p></li><li><p>request personally identifiable information through unsanctioned websites or applications;
</p></li><li><p>attempt to solicit money from you as part of the hiring process or as part of an employment offer;
</p></li><li><p>solicit money to complete visa requirements as part of a job offer.<br>
</p></li></ul><p><br>
If you receive unsolicited offers of employment from Commerce, we urge you to be extremely cautious and avoid engaging or responding.</p></div>

Senior Software Engineer

Accenture

<div><p><b>YOU ARE</b></p><p>
As a hands-on Infrastructure architect, you are an early-career engineer who learns and grows while contributing hands-on to the AI and machine learning infrastructure that powers real-world applications. Under the guidance of senior architects and engineers, you'll develop practical skills in coding, testing, configuring, deploying, monitoring, and troubleshooting AI systems and the infrastructure they run on. Day to day, you'll write and test code and deployment scripts, help configure cloud and on-premises compute resources such as GPU clusters and distributed training environments, deploy AI systems and models into production, and support data pipelines that feed AI and ML workflows. You'll learn to monitor AI systems and infrastructure health across both InfraOps and MLOps disciplines, perform AI monitoring to track model and system performance, and troubleshoot issues across the computational stack with mentorship and support. This is a hands-on, learning-focused where you build expertise across modern tools and platforms &mdash; including container orchestration, model serving, CI/CD pipelines, InfraOps, MLOps, and AI monitoring &mdash; while making meaningful contributions to infrastructure that enables AI-driven busin</p><p>
ess outcomes.</p><p></p><p><b>
THE WORK</b></p><ul><li>
Write, test, and debug code and scripts for AI infrastructure tasks, including automation and tooling, under the guidance of senior engineers.</li><li>
Develop and maintain infrastructure and software deployment scripts to support reliable, repeatable releases of AI systems and models.</li><li>
Configure and provision compute resources across cloud and on-premises environments, including GPU clusters and distributed training setups.</li><li>
Deploy AI systems and machine learning models into production infrastructure, following established processes and best practices.</li><li>
Deploy data pipelines that feed AI and ML workflows, ensuring data is available, clean, and reliable.</li><li>
Assist with container orchestration and model serving, learning tools such as Docker, Kubernetes, and model deployment frameworks.</li><li>
Support and maintain CI/CD pipelines for automating the build, test, and deployment of AI infrastructure and applications.</li><li>
Monitor AI systems and infrastructure health across InfraOps and MLOps disciplines, tracking performance, reliability, and resource utilization.</li><li>
Perform AI monitoring to track model performance, detect drift or degradation, and surface issues for review.</li><li>
Troubleshoot and help resolve issues across the computational stack &mdash; hardware, networking, software, and models &mdash; with mentorship and support.</li><li>
Document configurations, processes, and procedures to maintain clear, repeatable, and shareable knowledge across the team.</li><li>
Collaborate with senior architects and engineers, participating in code reviews, team discussions, and knowledge-sharing sessions to grow technical skills.</li><li>
Apply security, cost-efficiency, and scalability best practices as you learn them, contributing to well-managed and responsible infrastructure.</li></ul></div>
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<div><p><b>EDUCATION</b></p><ul><li>
Bachelor's Degree in Computer Science, Computer Engineering, related Engineering field</li></ul><p></p><p><b>
BASIC (REQUIRED) QUALIFICATION</b></p><ul><li>
Work or coursework experience with AI/ML or Computer engineering or Computer science.</li><li>
Coding, building, monitoring, troubleshooting applications of AI/ML models; selecting, designing and infrastructure for deploying and running them on premise or on public cloud.</li><li>
Strong understanding of AI and machine learning as a subject.</li><li>
Strong understanding of computing infrastructure a subject, preferred knowledge of AI infrastructure.</li><li>
Proficiency in programming languages such as Python, Java, or C++.</li></ul></div><p></p>

AI Infrastructure Architecture Analyst

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