Specialist Software Engineer - AI Systems
About this opportunity
Career Category
Information Systems
Job 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
Role Description:
We are seeking a highly skilled and experienced Senior Software Engineer with strong experience in designing, configuring, and building agentic AI systems, cloud-native software applications, and ML-enabled solutions. In this role, you will develop scalable software systems that leverage large language models, intelligent agents, workflow orchestration, APIs, cloud services, and MLOps practices.
The ideal candidate combines strong software engineering fundamentals with practical experience in AI/ML systems, including agent frameworks, retrieval-augmented generation, model integration, evaluation, deployment, monitoring, and automation. You will work closely with product teams, data scientists, ML engineers, platform teams, and business stakeholders to deliver secure, reliable, and maintainable AI-enabled software solutions.
Roles & Responsibilities:
Design, configure, and build agentic AI systems that can reason, plan, use tools, execute workflows, and interact with enterprise systems.
Develop scalable software applications and services using modern cloud-native architectures.
Integrate large language models, APIs, databases, vector stores, and orchestration frameworks into production-ready applications.
Build and maintain AI-enabled workflows using agent frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, or similar technologies.
Implement retrieval-augmented generation patterns, including document ingestion, chunking, embedding generation, vector search, reranking, and response generation.
Partner with data science and ML teams to operationalize machine learning models and AI capabilities into software products.
Apply MLOps practices for model deployment, monitoring, versioning, evaluation, governance, and continuous improvement.
Develop reusable components, APIs, services, and integration patterns to accelerate AI solution delivery.
Define and implement robust cloud architectures, preferably on AWS, using serverless, containerized, or microservices-based approaches.
Implement observability, logging, monitoring, error handling, and performance optimization for AI and ML-enabled applications.
Evaluate and improve agent performance, including prompt quality, tool selection, response accuracy, latency, cost, and reliability.
Functional Skills:
Must-Have Skills:
Strong hands-on software engineering experience with Python, JavaScript/TypeScript, SQL/NoSQL, APIs, and cloud-native application development.
Experience building or integrating applications with generative AI, LLMs, agentic workflows, RAG patterns, or AI orchestration frameworks.
Working knowledge of ML lifecycle concepts, including model deployment, evaluation, monitoring, versioning, and automation.
Experience with CI/CD, testing, containerization, observability, and production-grade software delivery.
Strong problem-solving, communication, collaboration, and technical ownership skills.
Good-to-Have Skills:
Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar agent frameworks.
Experience with vector databases, embeddings, semantic search, reranking, prompt engineering, fine-tuning, or LLM evaluation.
Experience with MLOps tools such as MLflow, SageMaker, Databricks, Kubeflow, Airflow, or similar platforms.
Familiarity with serverless, microservices, event-driven architecture, Kubernetes, or managed cloud AI/ML services.
Knowledge of responsible AI, model governance, human-in-the-loop workflows, security, privacy, and regulated environments.
Education and Professional Certifications
Bachelor’s or Master's degree in computer science and engineering preferred, other Engineering field is considered; 7 to 12 years of software development experience
Cloud Computing certificate preferred
Soft Skills:
Excellent analytical and troubleshooting skills.
Strong verbal and written communication skills
Ability to work effectively with global, virtual teams
High degree of initiative and self-motivation.
Ability to manage multiple priorities successfully.
Team-oriented, with a focus on achieving team goals
Strong presentation and public speaking skills.
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.
.
Job details
How this role compares
Computed from every other active Information Technology role in our database, not just this employer's listings.
We currently track 1097 comparable Information Technology roles across 55 biopharma companies.
Salary context
143 of 1097 peers report a salary range (USD, annualized)
Peers share this role's job function. This posting doesn't list a seniority level, so peers aren't narrowed by seniority either -- the range below may span more levels than usual.
Where these roles are based
Top locations among the 1097 comparable roles
+ 23 more countries
Seniority mix
612 of 1097 peers have a known seniority level
Therapeutic area mix
1 of 1097 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
Similar opportunities
The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.
How we calculate "similar"
No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.
Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.