At a Glance
- Tasks: Build AI solutions and optimise software for real-world applications in a dynamic environment.
- Company: Join Goldman Sachs, a leading global investment banking firm with a focus on innovation.
- Benefits: Enjoy competitive pay, health perks, remote work options, and opportunities for professional growth.
- Other info: Collaborate with global teams and enhance your skills in a fast-paced, supportive culture.
- Why this job: Make an impact by developing cutting-edge AI technologies that drive business success.
- Qualifications: Bachelor's degree in a computational field and 5+ years of relevant experience required.
The predicted salary is between 60000 - 80000 € per year.
Asset implement retrieval pipelines, prompt synthesis, response validation, and self-correction loops tailored to production operations. Integrate with runtime ecosystems: Connect agents to observability, incident management, and deployment systems to enable automated diagnostics, runbook execution, remediation, and post-incident summarization with full traceability.
Collaborate directly with users: Partner with production engineers and application teams to translate production pain points into agentic AI roadmaps; define objective functions linked to reliability, risk reduction, and cost; and deliver auditable, business-aligned outcomes.
Safety, reliability, and governance: Build validator models, adversarial prompts, and policy checks into the stack; enforce deterministic fallbacks, circuit breakers, and rollback strategies; instrument continuous evaluations for usefulness, correctness, and risk.
Scale and performance: Optimize cost and latency via prompt engineering, context management, caching, model routing, and distillation; leverage batching, streaming, and parallel tool-calls to meet stringent SLOs under real-world load.
Build a RAG pipeline: Curate domain-knowledge; build data-quality validation framework; establish feedback loops and milestone framework to maintain knowledge freshness.
Raise the bar: Drive design reviews, experiment rigor, and high-quality engineering practices; mentor peers on agent architectures, evaluation methodologies, and safe deployment patterns.
Qualifications
A Bachelor's degree (Masters/PhD preferred) in a computational field (Computer Science, Applied Mathematics, Engineering, or in a related quantitative discipline), with 5+ years of experience as an applied data scientist/machine learning engineer.
Essential Skills
- 3-5 years of software development in one or more languages (Python, C/C++, Go, Java); strong hands-on experience building and maintaining large-scale Python applications preferred.
- 3 years designing, architecting, testing, and launching production ML systems, including model deployment/serving, evaluation and monitoring, data processing pipelines, and model fine-tuning workflows.
- Practical experience with Large Language Models (LLMs): API integration, prompt engineering, finetuning/adaptation, and building applications using RAG and tool-using agents (vector retrieval, function calling, secure tool execution).
- Understanding of different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Qwen, Claude).
- Solid grasp of applied statistics, core ML concepts, algorithms, and data structures to deliver efficient and reliable solutions.
- Strong analytical problem-solving, ownership, and urgency; ability to communicate complex ideas simply and collaborate effectively across global teams with a focus on measurable business impact.
- Proficiency building and operating on cloud infrastructure (ideally AWS), including containerized services (ECS/EKS), serverless (Lambda), data services (S3, DynamoDB, Redshift), orchestration (Step Functions), model serving (SageMaker), and infra-as-code (Terraform/CloudFormation).
Asset & Wealth Management - Software Engineer, AI Platform and Services - Associate - Birmingham employer: Goldman Sachs Group, Inc.
Goldman Sachs is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of Birmingham. Employees benefit from extensive growth opportunities, mentorship programmes, and a commitment to diversity and inclusion, all while working on cutting-edge AI technologies that drive meaningful business outcomes. With a focus on safety, reliability, and governance, team members are empowered to push the boundaries of technology in a supportive environment that values their contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Asset & Wealth Management - Software Engineer, AI Platform and Services - Associate - Birmingham
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Goldman Sachs. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills in real-time! If you get the chance, do a coding challenge or a technical interview. It’s your moment to shine and demonstrate your expertise in Python and ML systems.
✨Tip Number 3
Prepare for behavioural questions! Think about your past experiences and how they relate to the role. Use the STAR method (Situation, Task, Action, Result) to structure your answers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining the team!
We think you need these skills to ace Asset & Wealth Management - Software Engineer, AI Platform and Services - Associate - Birmingham
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with AI platforms and software engineering. Use keywords from the job description to show we’re on the same page!
Showcase Your Skills:Don’t just list your skills; demonstrate them! Include specific examples of projects where you’ve implemented retrieval pipelines or worked with large-scale Python applications. We love seeing real-world applications of your expertise.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s relevant. Make it easy for us to see how you fit the role without wading through fluff.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our team!
How to prepare for a job interview at Goldman Sachs Group, Inc.
✨Know Your Tech Inside Out
Make sure you’re well-versed in the programming languages and technologies mentioned in the job description, especially Python and cloud infrastructure. Brush up on your experience with large-scale applications and be ready to discuss specific projects where you’ve implemented retrieval pipelines or worked with LLMs.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled complex problems in previous roles. Think about times when you translated production pain points into actionable solutions, and be ready to explain your thought process clearly. This will demonstrate your analytical skills and ownership.
✨Collaborate and Communicate
Since the role involves working closely with production engineers and application teams, practice articulating your ideas simply and effectively. Be prepared to discuss how you’ve collaborated in the past and how you can contribute to a team environment focused on measurable business impact.
✨Understand Safety and Governance
Familiarise yourself with concepts like validator models, policy checks, and circuit breakers. Be ready to discuss how you would implement safety measures in your work, as this is crucial for the role. Showing that you prioritise reliability and governance will set you apart.
