Bachelor's degree in Computer Science, Engineering, Data Science, or related field, or equivalent experience.
5+ years of professional software engineering experience with production-grade applications.
Hands-on experience with AWS and Azure cloud services.
Experience with Databricks, including data engineering and ML workflows.
Strong proficiency in a modern programming language (e.g., Python, SQL).
Demonstrated experience with generative AI and LLM-based applications.
Ability to work independently in ambiguous environments.
Responsibilities
Partner with stakeholders across various functions to identify and prioritize AI-driven solutions.
Design, build, and deploy AI workflows and applications from prototype to production.
Establish engineering practices and standards for AI solution delivery.
Collaborate with Data Platform Engineer to model and productionize data for AI solutions.
Work with DevOps Engineer to create CI/CD pipelines and monitoring for AI applications.
Leverage Databricks and AWS services to build agentic AI workflows.
Rapidly prototype proof-of-concepts, gather feedback, and iterate for production.
Document architecture and delivery patterns to create a repeatable internal playbook.
Benefits
Competitive salaries and excellent benefit package.
Full Job Description
The Position
This is a newly created, green-field role and the first Forward Deployed Engineer, AI hired within the company. The person in this role will partner directly with business and scientific stakeholders across multiple functions to identify high-value problems and build and deploy AI-driven solutions that solve them. Because there is no existing playbook for this function, the Forward Deployed Engineer will help define how AI solutions are scoped, built, and delivered internally, working hands-on across the AWS, Azure, Databricks, and Microsoft technology stack alongside the Data Platform Engineer, DevOps Engineer, and Databricks/AWS platform teams. This role requires someone comfortable operating with ambiguity, moving quickly from problem discovery to a working solution, and embedding directly with internal teams to understand their workflows before proposing and shipping AI tools that fit how they actually work.
Responsibilities
Partner directly with stakeholders across R&D, clinical, manufacturing, commercial, and other business functions to identify, scope, and prioritize opportunities for AI-driven internal solutions.
Design, build, and deploy agentic AI workflows and applications that solve real operational and scientific problems, working end-to-end from prototype through production.
Establish foundational engineering practices, standards, and reusable patterns for AI solution delivery, since this is the first role of its kind in the organization.
Work closely with the Data Platform Engineer to access, model, and productionize data needed for AI solutions across Databricks and AWS.
Collaborate with the DevOps Engineer to build reliable CI/CD pipelines, deployment processes, and monitoring for AI applications across AWS/ Databricks inside a MS environments.
Leverage the Databricks platform and AWS services (e.g., Bedrock, Lambda, S3) to build and orchestrate agentic AI workflows and applications, primarily by composing and integrating existing foundation models rather than training new ones.
Integrate solutions with Microsoft/Azure tools (e.g., Azure AI services, M365) where appropriate to meet business needs.
Rapidly prototype proof-of-concepts with internal teams, gather feedback, and iterate quickly to move validated solutions into production.
Document architecture, decisions, and delivery patterns to build a repeatable internal playbook for future forward-deployed engineering work.
Act as a hands-on technical resource embedded with business teams, translating ambiguous business problems into concrete technical solutions.
Requirements
Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience.
5+ years of professional software engineering experience, including building and deploying production-grade applications.
Hands-on experience with AWS cloud services and Azure/Microsoft cloud services.
Experience working with Databricks, including data engineering, notebooks, and/or ML workflows.
Strong proficiency in at least one modern programming language (e.g., Python, SQL, or similar) used for building data and AI applications.
Demonstrated experience building agentic workflows and applications with generative AI and LLM-based approaches (e.g., orchestration frameworks, tool use, retrieval-augmented generation) to solve practical business problems.
Proven ability to work independently in ambiguous, undefined environments and to build solutions from the ground up without an established playbook.
Strong cross-functional communication skills, with the ability to translate technical concepts for non-technical business stakeholders and vice versa.
Preferred
Knowledge of the pharmaceutical, biotech, or life sciences industry is desirable but not required.
Experience with Databricks certifications, AWS certifications, or Microsoft Azure certifications.
Prior experience in a "forward deployed engineer," solutions engineering, or embedded engineering role, working directly with business teams rather than in a purely centralized product function.
Experience with LLMOps/agent-ops tooling and practices for deploying, monitoring, and evaluating agentic workflows in production.
Familiarity with regulated-industry considerations (e.g., data privacy, validation, GxP) relevant to deploying AI solutions in a pharma environment.
Experience building internal tools, chatbots, or agentic AI applications using modern LLM frameworks.
A builder mindset with the initiative to define scope and process in a green-field function.
Wisconsin pay range
$155,000-$175,000 USD
California pay range
$175,000-$190,000 USD
Arrowhead provides competitive salaries and an excellent benefit package.
About Arrowhead Research
Arrowhead Research is a biotechnology company that develops RNA interference (RNAi) therapeutics. The company was founded in 2007 and is headquartered in Pasadena, California. Arrowhead's RNAi technology targets specific genes to silence their expression, which can be used to treat a variety of diseases. The company's pipeline includes treatments for liver disease, cancer, and cardiovascular disease. Arrowhead has partnerships with pharmaceutical companies such as Amgen and Janssen Pharmaceuticals. The company has received FDA approval for some of its products and is conducting clinical trials for others.
