One partner, one powerful solution.
Senior AI Engineer – STARLIMS AI Platform
Location
United States
Posted
11 days ago
Salary
0
Seniority
Senior
Job Description
Senior AI Engineer – STARLIMS AI Platform
STARLIMS
• Design and optimize RAG pipelines over domain-specific content • Improve retrieval quality, ranking, and grounding to reduce hallucinations • Build evaluation frameworks to measure accuracy and consistency • Work with fragmented enterprise data and make it usable • Build AI-powered features integrated into STARLIMS workflows • Design for reliability (latency, scale, model variability) • Implement guardrails, fallbacks, and observability • Manage prompt evolution, model drift, and regressions • Develop systems that can reason, call tools, and execute multi-step tasks • Integrate with internal APIs, developer tooling, and external systems • Build and operate backend services on AWS (Lambda, API Gateway, DynamoDB, etc.) • Own system architecture and key technical decisions • Contribute to infrastructure-as-code and deployment pipelines
Job Requirements
- 6+ years of software engineering experience, including production systems
- Experience building RAG systems beyond prototypes
- Strong understanding of LLM behavior, limitations, and failure modes
- Experience with LLM APIs and prompt/system design
- Solid backend and cloud experience (AWS or equivalent)
- Proficiency in TypeScript and/or Python
Benefits
- Competitive health and Wellness (medical, dental, and vision)
- Retirement plan with matching company contribution
- Life Insurance and Disability/Income Protection
Related Guides
Related Job Pages
More AI Engineer Jobs
Role Description We are seeking experienced AI Engineers to support a public sector healthcare initiative, delivering production-grade AI solutions in a highly regulated environment. This role focuses on real-world impact, building systems that operate within strict privacy, security, and governance frameworks. This is not a research role—you will be responsible for deploying and operationalizing AI in production within an enterprise Azure ecosystem. What You’ll Be Doing in the Role - Design, build, and deploy production AI/ML solutions in Azure - Work with Azure ML / Azure AI services across the full lifecycle (training, deployment, monitoring, retraining) - Integrate models into secure enterprise systems (APIs, backend services, data pipelines) - Handle healthcare and regulated data, ensuring compliance with privacy and security standards - Collaborate with data engineers on large-scale data platforms (e.g., Databricks, ETL pipelines) - Implement responsible AI practices, including explainability, bias mitigation, and auditability - Work within public sector delivery structures, engaging with architects, developers, and non-technical stakeholders Qualifications - Proven experience delivering AI/ML solutions in production environments - Hands-on experience with Azure ML / Azure AI (strongly preferred) - Experience working with regulated data environments (healthcare, government, or similar) - Strong understanding of model deployment, monitoring, and lifecycle management - Experience integrating AI into operational systems, not just building models - Ability to work in structured, compliance-driven environments Nice to Have - Experience with clinical/NLP data or healthcare analytics - Familiarity with FHIR and healthcare interoperability standards - Exposure to population health, risk modeling, or patient outcomes use cases - Experience implementing GenAI/LLM solutions in secure enterprise environments And You Are... - Always improving your skills and knowledge: you want to be the best at what you do - Curious and creative; comfortable taking on new problems and challenges - A self-starter with the ability to recommend priorities to the project leader - Comfortable working through problems and figuring things out with minimal supervision - Great problem-solving skills: thorough and reliable - Able to work in a team: share knowledge and assist other team members - A good communicator: able to explain your ideas and recommendations - Well organized and dependable under pressure: you manage your time effectively - Energized by our company values! Benefits - A values-driven workplace where people really matter. - Flexible work location - Support for remote work/work from home. - Competitive salary, retirement savings program, and rewards program - Comprehensive health, dental, vision, life and disability insurance plans and access to e-health care - Paid vacation, maternity/parental leave, paid sick leave and paid Mariner MyLife days. - Unlimited training
AI Architect
Cyclotron, Inc.Cyclotron, Inc., founded in 2014, is a technology consultancy firm specializing in IT strategy, cloud collaboration, security, and digital transformation solutions. With a mission
• Own the architecture on AI engagements • Serve as a credible technical voice with client stakeholders • Run workshops and design reviews • Architect agentic systems, RAG pipelines, and AI-augmented workflows • Contribute to reference architectures, skills, prompts, and MCP servers • Help build out our growing OpenAI and Anthropic practices • Pair with senior architects and engineers on the hard parts • Translate between business goals and engineering reality • Write clearly, present crisply, disagree well • Contribute to internal IP.
AI Engineering Intern
Phil, Inc.Medication Access, Simplified. We are on a mission to help people get their medications quickly, easily and affordably.
• Assist in the design, development, testing, and deployment of AI/ML models and applications • Collaborate with Engineering, IT, and business stakeholders to translate business needs into technical solutions • Build and optimize data pipelines and inference workflows • Develop prototypes and AI-powered applications within cloud environments such as AWS • Work with both structured and unstructured datasets, including text, APIs, and image-based data • Experiment with large language models (LLMs), prompt engineering techniques, and AI APIs • Document code, experiments, and technical findings for team collaboration and knowledge sharing • Participate in code reviews, sprint planning, and technical discussions with the Engineering team • Present project work and findings to technical and business stakeholders • Support additional projects and initiatives as needed across the department
Sr. Delivery Acceleration AI Engineer
ServiceNowAs the AI platform for business transformation, we're putting AI to work across organizations — freeing people for work that matters. Making old tech work with new tech. Reaching across departments, from the front office to the back office and every office in between. Our ambition? To become the AI defining enterprise software company of the 21st century (or "AI DESCO21C," as we like to call it). With more than 8,100+ customers, we serve approximately 85% of the Fortune 500®, and we're proud to be a Fortune 100 Best Companies to Work For® and World's Most Admired Companies™. Explore your future career with us, visit www.servicenow.com/careers. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.
Company Description It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today - ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone. Job Description ROLE DESCRIPTION As a Sr. Delivery Acceleration AI Engineer, you will design, develop, and optimize AI-powered autonomous implementation solutions that transform how ServiceNow Expert Services deliver customer implementations. Working within the Delivery Acceleration team, you'll focus on building and refining AI agents that automate ServiceNow configuration, generate implementation artifacts, and accelerate time-to-deploy-turning what previously required weeks of manual effort into AI-driven delivery that produces production-ready outputs in hours. This role requires deep expertise in prompt engineering, AI agent architecture, and an understanding of enterprise professional services delivery. You'll work directly with autonomous implementation platforms built on large language models to create, test, and refine the AI-driven workflows that generate ServiceNow configurations, user stories, test scripts, and deployment packages for customer engagements. Critically, you must understand the professional services go-to-market motion-how services are scoped, sold, estimated, and delivered-because the AI solutions you build must align with how consultants and sales teams position and execute customer engagements. Your work directly impacts delivery speed, quality, margin, and the customer experience. Success requires balancing technical depth in AI/LLM systems with practical business acumen. You'll operate in a fast-paced sprint cadence where AI capabilities evolve rapidly, requiring continuous experimentation, rigorous quality validation, and close collaboration with solution architects, product managers, and delivery consultants across AMS, EMEA, and APAC+JPN. You will partner closely with the platform administrator who owns operations, adoption, and governance for the AI-powered deal and delivery document generator, ensuring the AI agents and prompt assets you build are deployed, scaled, and governed effectively across the global delivery community. WHAT YOU GET TO DO IN THIS ROLE: Design & Develop AI-Powered Implementation Agents - Architect and build AI agent workflows that autonomously generate ServiceNow configurations, implementation plans, user stories, and test scripts from customer requirements - Develop, test, and iterate sophisticated prompt chains and orchestration patterns that produce consistent, production-quality outputs across ServiceNow product workflows (ITSM, CSM, HRSD, SPM, etc.) - Design multi-step agentic processes that handle complex implementation logic-scope validation, dependency mapping, configuration generation, and quality assurance-with minimal human intervention - Build and maintain prompt libraries, templates, and reusable patterns that encode delivery best practices and Gold Implementation standards into AI agent behavior, partnering with the platform administrator on library structure, versioning, and publication to end users - Partner with AI Architects and Solution Architects to ensure agent outputs align with ServiceNow platform strategy, product direction, and enterprise readiness standards Lead Prompt Engineering & AI Quality Optimization - Serve as a subject matter expert in prompt engineering techniques for large language models, including chain-of-thought reasoning, few-shot learning, structured output generation, and context window optimization - Design and execute systematic prompt evaluation frameworks that measure output accuracy, consistency, completeness, and adherence to ServiceNow implementation standards - Continuously optimize prompt performance through A/B testing, output analysis, and iterative refinement-treating prompts as production code with version control and quality gates, incorporating user feedback and quality-audit signals surfaced by the platform administrator and the champions network - Develop guardrails and validation logic that ensure AI-generated configurations meet enterprise quality standards before being deployed to the Expert Services community - Stay current on evolving platform capabilities and techniques, rapidly incorporating new approaches that improve agent accuracy and efficiency Integrate AI Solutions with Professional Services GTM & Delivery - Understand the full professional services lifecycle-from pre-sales scoping and estimation through delivery execution and go-live-and ensure AI agent capabilities map to real engagement workflows - Design AI solutions that support accurate estimation by providing data on automated vs. manual effort, enabling services sales teams to right-size engagements - Partner with delivery consultants to validate that AI-generated outputs are usable in real customer contexts, incorporating feedback into continuous improvement cycles - Contribute to packaging AI-accelerated delivery into repeatable service offerings that can be positioned and sold by services and license sales teams Build Platform Integrations & Delivery Automation - Integrate AI agent outputs with the ServiceNow platform, customer engagement portals, and internal delivery systems to create seamless end-to-end automation - Design APIs, data pipelines, and integration patterns that connect autonomous implementation tools with estimation systems, resource management platforms, and project tracking tools - Build automated testing and validation workflows that verify AI-generated configurations against ServiceNow best practices and customer requirements before deployment - Collaborate with the implementation platform team to embed AI capabilities into the customer and partner delivery experience - Ensure all integrations meet enterprise security, data governance, and compliance standards - Coordinate with the platform administrator on release management-staging validation, production rollout, and vendor escalation-so new AI capabilities reach users without disrupting platform stability Drive Measurement & Continuous Improvement - Establish quality metrics for AI agent outputs: accuracy rates, rework percentages, time savings, and customer acceptance rates, feeding these signals into the adoption and ROI metrics the platform administrator reports to A&M leadership - Analyze agent performance data to identify improvement opportunities, failure patterns, and expansion use cases - Contribute to the delivery acceleration roadmap by identifying where AI can fill capability gaps or replace manual processes - Document engineering best practices, architectural patterns, and lessons learned to build organizational knowledge - Participate in sprint ceremonies, code reviews, and cross-team collaboration in a two-week sprint cadence with monthly releases Qualifications To be successful in this role you have: - 5+ years of experience in software engineering, AI/ML engineering, or technical consulting in enterprise software environments - 2+ years of hands-on experience with large language models, prompt engineering, and AI agent development-not just using AI tools, but building production systems on top of them - Demonstrated expertise in prompt engineering techniques: chain-of-thought reasoning, structured output generation, few-shot/zero-shot patterns, context window management, and systematic prompt evaluation - Strong understanding of professional services delivery operations: how engagements are scoped, sold, estimated, staffed, and delivered - Experience with API design, system integration, and building data pipelines that connect AI outputs to enterprise workflows - Proficiency in Python, JavaScript/TypeScript, or similar languages used in AI agent development and automation - Understanding of ServiceNow platform architecture, data models, and configuration patterns - Excellent communication skills-ability to translate technical AI capabilities into business impact for non-technical stakeholders - Experience working in agile, sprint-based environments with measurable delivery outcomes Not required but nice to have: - Experience building autonomous implementation or code generation systems that produce production-ready outputs - Background in management consulting or professional services delivery operations - Familiarity with ServiceNow implementation methodology and delivery best practices - Experience with AI agent orchestration frameworks and multi-step workflow automation - Knowledge of AI ethics, output validation, responsible AI practices, and enterprise governance requirements - ServiceNow platform certifications (CSA, CIS, or similar) - Experience with enterprise estimation tools, resource management platforms, or delivery automation systems Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.



