Asset & Wealth Management - Software Engineer, AI Platform and Services - Associate - Richardso[...]

Goldman Sachs Bank AG; Richardson (TX); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

Health insurance

Retirement savings assistance

On-site child care services

Fitness reimbursement

Job summary

Goldman Sachs Bank AG is looking for a Software Engineer for their AI Platform and Services team in Richardson, TX. This role focuses on leveraging AI models to enhance program delivery and involves building agentic AI systems, working closely with production teams to optimize solutions.

Qualified candidates will have a Bachelor’s degree in a related field, over 5 years of software development experience in Python, and practical skills with Large Language Models. The role offers a comprehensive benefits package, including health insurance and retirement planning assistance.

Qualifications

• 5+ years of experience as an applied data scientist or machine learning engineer.
• Experience building and maintaining large-scale Python applications.
• Practical experience with Large Language Models (LLMs).

Responsibilities

• Design and implement tool-calling agents for AI systems.
• Build evaluation framework for open-source and foundational LLMs.
• Partner with production engineers to define AI roadmaps.

Skills

Software development in Python

Model deployment/serving

Prompt engineering

Problem-solving

Cloud infrastructure (AWS)

Education

Bachelor’s degree in a computational field

Master’s or PhD

Tools

Python

AWS

Terraform

Job description

Asset & Wealth Management – Software Engineer, AI Platform and Services – Associate (Richardson, TX)

AI Platform and Services VP will provide thought leadership across the organization, with regards to concrete opportunities to use and leverage AI models and tools to accelerate program delivery end to end. The role includes providing and influencing product, strategic direction and roadmap.

In this role, you will be responsible for launching and implementing GenAI agentic solutions aimed at reducing the risk and cost of managing large‑scale production environments with varying complexities. You will address various production runtime challenges by developing agentic AI solutions that can diagnose, reason and take actions in production environments to improve productivity and address issues related to production support.

What you’ll do

• Build agentic AI systems: Design and implement tool‑calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol. Engineer robust guardrails for safety, compliance and least‑privilege access.
• Productionize LLMs: Build evaluation framework for open‑source and foundational LLMs; 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 (Master’s or PhD preferred) in a computational field (Computer Science, Applied Mathematics, Engineering or a related quantitative discipline), with 5+ years of experience as an applied data scientist or machine learning engineer.

Essential Skills

• 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.
• 5+ 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, fine‑tuning/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).

Goldman Sachs is an equal‑intention employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veteran status, disability or any other characteristic protected by applicable law.

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process.

Healthcare & Medical Insurance

We offer a wide range of health and welfare programs that vary depending on office location. These generally include medical, dental, short‑term disability, long‑term disability, life, accidental death, labour accident and business travel accident insurance.

Financial Wellness & Retirement

We assist employees in saving and planning for retirement, offer financial support for higher education and provide a number of benefits to help employees prepare for the unexpected. We offer live financial education and content on a variety of topics to address the spectrum of employees’s priorities.

Health Services

We offer a medical advocacy service for employees and family members facing critical health situations, and counseling and referral services through the Employee Assistance Program (EAP). We provide Global Medical, Security and Travel Assistance and a Workplace Ergonomics Program. We also offer state‑of‑the‑art on‑site health centers in certain offices.

Fitness

To encourage employees to live a healthy and active lifestyle, some of our offices feature on‑site fitness centers. For eligible employees we typically reimburse fees paid for a fitness club membership or activity (up to a pre‑approved amount).

Child Care & Family Care

We offer on‑site child care centers that provide full‑time and emergency back‑up care, as well as mother and baby rooms and homework rooms. In every office, we provide advice and counseling services, expectant parent resources and transitional programs for parents returning from parental leave. Adoption, surrogacy, egg donation and egg retrieval stipends are also available.

Benefits at Goldman Sachs

Read more about the full suite of class‑leading benefits our firm has to offer.