Role Description
The Specialist Software Engineer will be responsible for designing, developing, and evolving next-generation AI-powered scientific authoring platforms supporting Research and Preclinical organizations. This role will play a critical part in scaling internal Amgen's AI solutions within Research domains.
The successful candidate will work closely with scientists, informaticians, product managers, architects, and engineering teams to build enterprise-grade AI solutions leveraging Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), agentic workflows, knowledge management systems, and cloud-native architectures.
This role requires strong expertise in AI platform engineering, distributed systems, scientific document processing, and cloud technologies. The candidate will provide technical leadership in architecting scalable, reliable, and compliant AI solutions that improve scientific productivity and accelerate research outcomes.
Roles & Responsibilities
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Design full stack solution with scalable backend services, APIs, and distributed systems supporting AI-driven workflows.
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Lead architecture decisions around scalability, reliability, security, observability, and maintainability.
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Develop Retrieval-Augmented Generation (RAG) pipelines, vector search solutions, and semantic retrieval frameworks.
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Build and optimize multi-agent workflows for content generation, critique, review, and refinement.
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Implement source attribution, traceability, and grounding mechanisms for AI-generated content.
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Develop prompt orchestration, tool integration, and agent execution frameworks.
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Design and implement document ingestion, semantic chunking, embedding generation, and indexing pipelines.
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Build cloud-native applications leveraging AWS services and modern engineering practices.
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Drive software quality through testing, code reviews, and engineering best practices.
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Design and implement AI-powered scientific authoring and knowledge management platforms.
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Develop integrations with scientific and enterprise data sources.
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Optimize retrieval quality through metadata filtering, hybrid search, and reranking techniques.
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Support structured and unstructured scientific content processing.
Basic Qualifications and Experience
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Master's or Bachelor's degree and 8-12 years of Information Systems experience
Preferred Qualifications and Experience
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8+ years of software engineering experience building enterprise applications.
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2+ years of hands-on experience developing Generative AI or LLM-powered applications implementing RAG concept.
Functional Skills:
Must-Have Skills
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Strong proficiency in Python.
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Experience developing scalable backend applications using Python, Java, or related technologies.
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Strong API design and microservices development experience.
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Strong SQL skills and database design experience.
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Hands-on experience with Large Language Models (LLMs) and Generative AI platforms.
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Experience implementing RAG architectures and semantic retrieval systems.
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Experience with vector databases such as PGVector, Pinecone, Weaviate, or OpenSearch Vector.
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Experience with agent orchestration frameworks such as LangGraph, Semantic Kernel, CrewAI, or equivalent.
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Strong understanding of prompt engineering, grounding, and AI evaluation methodologies.
Cloud & Platform Engineering
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Hands-on experience with AWS services such as S3, RDS, ECS/EKS, Lambda, IAM, CloudWatch, and EventBridge.
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Experience building cloud-native and distributed systems.
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Experience with containerization technologies including Docker and Kubernetes.
Good-to-Have Skills
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Experience with scientific document processing and OCR technologies.
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Experience with Amazon Bedrock, OpenAI, Anthropic Claude, or equivalent AI platforms.
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Experience with Terraform, CloudFormation, or Infrastructure as Code (IaC) practices.
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Experience with CI/CD pipelines and DevOps methodologies.
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Experience with monitoring and observability tools such as Splunk, Grafana, Prometheus, Datadog, or CloudWatch.
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Experience with scientific authoring, regulatory content management, PKDM, Toxicology, or Research Informatics platforms.
Professional Certifications (Preferred):
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AWS Certified Solutions Architect – Associate or Professional
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AWS Machine Learning Specialty
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Generative AI or Cloud AI certifications
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Kubernetes certifications (CKA/CKAD)
Soft Skills
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Strong problem-solving and analytical skills.
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Ability to translate complex scientific and business requirements into technical solutions.
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Excellent communication and stakeholder management skills.
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Ability to work effectively with global cross-functional teams.
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High degree of ownership and technical leadership.
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Ability to influence architecture and engineering decisions.
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Strong mentoring and collaboration skills.
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Ability to manage multiple priorities in a fast-paced environment.
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.
