> Markdown version of [/jobs/ext/2696177-agentic-workflow-engineer](https://www.wearedevelopers.com/jobs/ext/2696177-agentic-workflow-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Agentic Workflow Engineer - **Company:** Johnson & Johnson - **Location:** Cambridge, MA, United States - **Experience:** Expert - **Salary:** $109,000.0 - $174,800.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Data Stores, DevOps, Cyber-physical Systems, Robotic Automation Software, Management of Software Versions, Workflow Management Systems, Large Language Models, Generative AI, Information Technology, Machine Learning Operations, Data Pipelines - **Published:** September 3, 2026 - **Apply:** https://www.dice.com/job-detail/0a8b48ac-324b-424a-86ce-9f958feafdd3 ## About the Role * Master's or Ph.D. in Computer Science, Engineering, or a related computational field (or Bachelor's with substantial relevant experience). * At least 2 years experience building scientific workflow orchestration, or automation software, including experience in agentic workflows. * Hands-on experience designing real-time or near-real-time data pipelines and integrating complex and heterogeneous scientific data and instrument outputs. * Experience applying agentic AI and modern LLM-based agents (or comparable intelligent-automation systems) to scientific or laboratory workflows. * Experience working with enterprise or shared GenAI platforms and retrieval-augmented approaches (e.g., RAG or GraphRAG) rather than standing up capabilities from scratch. * Strong communication skills and comfort operating in ambiguity within a matrixed organization. Preferred * Experience in drug discovery domains such as biologics, high-throughput experimentation, or imaging. * Exposure to lab automation, robotic systems, or cyber-physical systems for R&D. * Familiarity with MLOps/DevOps, workflow engines, and production-grade monitoring/observability. * Understanding of FAIR data, ontologies, semantic models, lineage/provenance, and AI-ready data standards. This position will be based at one of our office locations in either Spring House, PA (strongly preferred), Titusville, NJ, Raritan, NJ, or Cambridge, MA, USA; or at our office in Madrid, Spain. (No remote option.) ## Description As a Senior Agentic Workflow Engineer, you will build and maintain agentic workflows and orchestration that support the scientific data analysis and secondary processing logic our team delivers. You will implement automation and AI pipelines connecting automation software, data stores, models, and compute, working closely with senior engineers to translate scientific priorities into working systems. You will partner across Discovery, Data Science, In Silico Discovery (ISD), our Enterprise Generative AI team, and our data-infrastructure and lab-automation teams to help enable closed-loop feedback so that each experimental cycle improves downstream models and decisions., Agentic Orchestration & Integration * Build and continuously improve agentic workflows that automate secondary analysis for biologics discovery assays, replacing fragile manual and ad-hoc scripted steps. * Develop and maintain real-time or near-real-time pipelines connecting automation software, data stores, models, and compute environments. * Partner with IT and platform teams to implement resilient APIs, observability, versioning, and workflow orchestration end-to-end. * Work with our Enterprise Generative AI team to build on shared GenAI platforms, models, and agentic frameworks - extending them for biologics discovery rather than duplicating enterprise capabilities. * Partner with ontology and MLOps colleagues so automated workflows produce semantically consistent, reusable data and deploy reliably into production. AI-Driven Scientific Learning * Contribute to workflows optimized for AI-driven learning, not just throughput, supporting closed-loop feedback across the design-make-test-learn (DMTL) cycle. * Collaborate with discovery scientists, AI/ML scientists, and data engineers so experimental outputs improve downstream property models and decision-making. * Help ensure data generated through agentic workflows is high-quality, traceable, interoperable, and AI-ready, with strong metadata, provenance, and lineage. * Identify and propose opportunities to apply agentic AI to compress cycle time and improve reproducibility. ## Related Videos - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1520-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Rethinking Workflows in the Agentic Era](https://www.wearedevelopers.com/videos/1540-rethinking-workflows-in-the-agentic-era) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) - [Building a Multi-Agent Orchestration Engine That Actually Follows the Rules](https://www.wearedevelopers.com/videos/100159-building-a-multi-agent-orchestration-engine-that-actually-follows-the-rules) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)