1 day ago
Base Salary
$81k - $110k/yr
Responsibilities
- Lead discovery by defining workflows, users, outcomes, acceptance criteria, constraints, data readiness, dependencies, and production implications.
- Translate complex problems into solution designs, delivery plans, technical workstreams, estimates, milestones, risks, release approaches, and support transitions.
- Build, prototype, review, or contribute to production AI applications, RAG systems, bounded agents, intelligent automation, APIs, and integrations.
- Maintain architecture across applications, workflows, data and knowledge pipelines, models, retrieval, agents, APIs, enterprise integrations, identity, access controls, observability, and human review.
- Coordinate full-stack software and AI engineering, data science, ML and context engineering, testing, platform, security, compliance, and business teams.
- Establish functional, performance, security, data, model, retrieval, generation, tool-use, human-oversight, and operational testing and evaluation thresholds.
- Coordinate production readiness through staged releases, monitoring, logging, SLOs, rollback, recovery, runbooks, issue triage, stabilization, and operational transition.
- Communicate evidence, risks, trade-offs, uncertainty, and status while measuring adoption and value and developing reusable standards, components, documentation, and playbooks.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or a diploma with 2+ years of relevant experience.
- Strong hands-on proficiency in Python and SQL and experience designing or reviewing production software, APIs, services, data flows, evaluation pipelines, and enterprise integrations.
- Experience with enterprise solution architecture, integration across applications and services, AI/ML and GenAI engineering, cloud-native lifecycle operations, and production readiness.
- Advanced capability in at least one of applied AI/ML, GenAI/RAG/agents, full-stack and integration engineering, or AI platform/MLOps, with breadth across the production lifecycle.
- Experience with hybrid or graph retrieval, knowledge graphs, source verification, MCP-style integration, durable or multi-agent workflows, policy enforcement, and adversarial testing is preferred.
- Experience with Databricks, AWS, Spark, LLMs, and agentic development solutions is preferred.
- Experience in life sciences, healthcare, payor, or pharmaceutical environments is a plus.
- Ability to provide hands-on technical leadership, exercise sound judgment, navigate ambiguity, coordinate multidisciplinary teams, and communicate risks, trade-offs, limitations, and delivery status clearly.
Benefits
- Comprehensive benefits including retirement and savings contributions, medical, dental and vision coverage, life and disability insurance, and flexible spending accounts.
- Eligibility-based discretionary annual bonus program or sales-based incentive plan for field sales representatives.
- Stock-based long-term incentives.
- Award-winning time-off plans.
- Flexible work models where possible, subject to the posting’s work location type.
- Career development opportunities and work/life balance support.
Tech Stack
Categories
About Amgen
Amgen is a public biotechnology company that discovers, develops, manufactures, and sells biologic and biosimilar therapeutics for patients with serious diseases. Its portfolio and pipeline span oncology, cardiovascular disease, osteoporosis, inflammation, and rare diseases, marketed globally through direct sales and partnerships. Founded in 1980 and headquartered in Thousand Oaks, California (NASDAQ: AMGN), Amgen is a component of the Dow Jones Industrial Average and completed the acquisition of Horizon Therapeutics in 2023.