Posted 1 day ago
Sr Associate Software Engineer
AI Summary
Designs, develops, tests, deploys, and supports secure, scalable GenAI solutions including LLM-powered assistants, agents, Custom GPTs, and RAG applications on enterprise platforms.
About this role
Career Category
Information SystemsJob Description
ABOUT AMGEN
Amgen harnesses the best of biology and technology to fight the world's toughest diseases, and make people's lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what's known today.
ABOUT THE ROLE
The Senior Associate Software Engineer is a hands-on software engineering contributor within the Applied AI - AI Productivity and Custom GPT Solutions Practice. The role designs, develops, tests, deploys, and supports secure, scalable, intuitive, and reusable GenAI solutions, including LLM-powered assistants, agents, Custom GPTs, retrieval-augmented generation (RAG) applications, and associated AI capabilities on approved enterprise platforms.
RESPONSIBILITIES
GenAI Solution Delivery
- Design, develop, test, and deploy LLM-powered assistants, agents, Custom GPTs, RAG solutions, APIs, and AI-enabled applications on ChatGPT Enterprise and other approved platforms.
- Implement prompt and context strategies, structured outputs, embeddings, vector or hybrid retrieval, tool calling, workflow orchestration, and human-in-the-loop controls.
- Build scalable RAG pipelines that ground responses in trusted enterprise data.
- Contribute to the GenAI capability roadmap through implementation of MCP-based Apps, ChatGPT Skills, plugins, Workspace Agents, and reusable integration patterns.
- Develop integration layers and event-driven workflows using APIs, RPA, n8n, and approved orchestration tools to connect systems and trigger agent workflows.
- Develop reusable Python services, libraries, templates, and evaluation utilities, and contribute TypeScript, React, or Next.js components when required by the solution.
Quality, Security, and Operations
- Implement automated unit, integration evaluation, and end-to-end tests, along with tracing and monitoring for retrieval quality, response consistency and reliability.
- Implement safeguards for prompt injection, data leakage, unauthorized retrieval, insecure tool execution, secrets exposure, excessive agency, and inappropriate model outputs.
- Apply secure integration and identity patterns using API gateways, OAuth, service identities, delegated authorization, role-based access control, secrets management, least privilege, and user-level auditability.
- Build and maintain CI/CD pipelines and approved cloud deployment configurations using AWS services, containers, serverless compute, or managed platform capabilities.
- Troubleshoot defects across application, model, retrieval, data, integration, and infrastructure layers; support incident investigation, remediation, rollback, patching, and performance tuning.
- Create and maintain technical designs, test evidence, runbooks, deployment instructions, and handover materials that support sustainable operations.
Collaboration and Enablement
- Partner with functional teams, product owners, architects, business SMEs, data engineers, platform teams, DevOps, cybersecurity, privacy, and responsible AI stakeholders to translate requirements into reliable solutions.
- Participate in agile planning, backlog refinement, estimation, demonstrations, retrospectives, release activities, and technical design reviews.
- Review code and technical designs, apply software engineering standards, and use AI-assisted development tools such as OpenAI Codex or GitHub Copilot with appropriate review, security, and quality controls.
- Support office hours, technical enablement sessions, junior engineers, and knowledge-sharing through reusable examples, engineering patterns, and lessons learned.
- Communicate delivery status, technical risks, dependencies, defects, and recommendations clearly to technical and non-technical stakeholders.
REQUIRED SKILLS AND QUALIFICATIONS
Basic Qualifications
- Master's degree with 4 or more years of relevant experience in Computer Science, Information Technology, Engineering, Data Science, or a related field; or
- Bachelor's degree with 6 or more years of relevant experience in Computer Science, Information Technology, Engineering, Data Science, or a related field.
Must-Have Skills
- 4 or more years of professional experience in software development, application engineering, systems integration, or system design.
- 2 or more years of hands-on experience building, deploying, or supporting production GenAI applications, assistants, agents, Custom GPTs, RAG solutions, or comparable AI-enabled software.
- Strong hands-on proficiency in Python and experience developing, testing, debugging, and maintaining production applications, APIs, data services, or integration components.
- Hands-on experience with prompt and context design, embeddings, vector databases or search, retrieval pipelines, structured outputs, tool integration, agent orchestration, evaluation, guardrails, and observability.
- Experience designing and building cloud-native solutions, preferably on AWS, using services such as Amazon Bedrock, AWS Lambda, Amazon EKS or ECS, API Gateway, IAM, networking, monitoring, and event-driven integration.
- Experience designing secure RESTful or GraphQL integrations using API gateways, OAuth, service identities, enterprise authentication, role-based access, secrets management, and least-privilege principles.
- Experience with automated testing, source control, code review, Git-based workflows, CI/CD, and responsible use of AI-assisted software development tools.
- Experience building modern web applications using TypeScript, React, Next.js, component-driven architecture, state management, design systems, and API integration.
- Working knowledge of SQL, files, databases, and governed data-access patterns, with strong troubleshooting and analytical skills across application, model, data, integration, and infrastructure layers.
Professional Skills
- Strong verbal and written communication skills and the ability to produce clear technical documentation.
- Ability to collaborate effectively with global, distributed, cross-functional teams using agile or scaled agile ways of working.
- High degree of initiative, adaptability, ownership, and self-motivation while delivering high-quality outcomes with appropriate guidance.
- Ability to manage multiple priorities, assess gaps and fit, communicate technical risks and tradeoffs, and support shared team outcomes.
Preferred Qualifications
- Experience with OpenAI APIs and SDKs, MCP servers and Apps, ChatGPT Skills, plugins, Workspace Agents, LangChain, LangGraph, n8n, or comparable agent technologies.
- Experience with Amazon Bedrock and related agent capabilities, AWS Lambda, Amazon EKS or ECS, Amazon EC2, API Gateway, IAM, VPC networking, or event-driven services.
- Experience with Databricks, Unity Catalog, Vector Search, SQL Warehouses, semantic layers, or governed natural-language-to-SQL solutions.
- Experience with Power Automate, UiPath, Tableau, Jira, Smartsheet, or comparable automation and delivery tools.
- Experience with model and application evaluation, red teaming, responsible AI, AI security, GxP, computer-system validation, regulated technology environments, or relevant technical certifications.
EQUAL OPPORTUNITY STATEMENT
Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.
We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.
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