Title: AI/ML Engineer - Python / Agentic AI - Remote Nationwide or Hybrid in MN/DC Requisition number: 2357479 Job category: Technology Primary location: Minnetonka, MN Overtime status: Exempt Travel: No Job Description: Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together. We are seeking an AI/ML Engineer with deep expertise in Generative AI technologies to develop and deploy cutting-edge solutions within the Optum Care Strategic Platform (Facets). The ideal candidate will have hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and frameworks such as LangGraph and LangChain. Strong proficiency in Python along with Software Engineering background using SQL and API development are essential. This role will involve close collaboration with Claims Operations. You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week. Primary Responsibilities: - Be able to understand the Facets Delivery, Client priority and requirements - Proven Good in adapting & adopting new technology footprints to optimize business solutions using AI Adoption - Apply a solid understanding of Agentic AI concepts and frameworks such as LangGraph and LangChain to design and implement intelligent, autonomous systems - Utilize expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Transformer architectures to build scalable and high-performing AI solutions - Develop sophisticated generative AI algorithms and models to create new data samples, patterns, or content based on existing datasets and user inputs - Build and maintain robust APIs using frameworks such as FastAPI to enable seamless integration of AI services - Develop secure, maintainable software using SQL and modern engineering patterns - Deploy AI/ML solutions in production environments, preferably on cloud platforms like Azure - Implement machine learning and natural language processing projects from concept to production - Conduct rigorous model testing, validation, and performance optimization - Containerize AI/ML projects and implement CI/CD pipelines using tools like GitHub Actions - Collaborate with stakeholders to preprocess, analyze, and interpret large-scale datasets - Stay current with emerging trends and advancements in generative AI and ML technologies - Mentor and lead other engineers to reach their potential - Ensure code quality and security by identifying and resolving vulnerabilities - Maintain solid programming practices and standards - Provide timely updates on tasks to reporting supervisor - Adherence to the defined SLA Compliance etc - Provide support and leadership in critical production support issue resolution - Participate in on-call rotations as scheduled - Work with team to achieve timely resolution of all production issues meeting or exceeding Service Level Agreements You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in. Required Qualifications: - Undergraduate degree or equivalent experience - 3+ years of experience in Python programming - 2+ years of experience with build, Deploying and manage ML models on cloud platforms such as Microsoft Azure or any other Cloud platform - 2+ years of Database Design/Programming - 1+ years of Terraform scripts understanding - 1+ years of Git action and CI/CD experience needed Preferred Qualifications: - 2+ years of software engineering and testing experience in C# / .Net programming language - Healthcare Claims EDI Experience - Prompt engineering experience - Experience leveraging Large Language Models (LLMs) - Experience working with various AI/ML infrastructure, tools and platforms across the full stack of AI/ML technology - Experience with the challenges of delivering and monitoring LLM based cloud systems into production - Proven solid communication skills with the ability to explain complex technical concepts to diverse audiences - All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy. Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $98,500 to $176,000 annually based on full-time employment. We comply with all minimum wage laws as applicable. At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission. UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Lead AI engineer Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realise their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Overview The CNPF Data & AI organisation is looking for a Lead AI Engineering Engineer to drive hands-on delivery of applied AI and agentic capabilities across our platforms. This role sits at the intersection of software engineering, machine learning engineering, and applied data science, with a strong emphasis on building production-grade AI systems. This is a senior individual contributor and technical leadership role. You will lead by example through deep hands-on engineering, influence technical direction, and partner closely with Applied AI, Data Science, and Product teams to take AI solutions from experimentation to secure, scalable production. Role • Lead hands-on development of AI and agentic systems from design through production deployment• Build and operate ML/AI services, pipelines, and APIs using strong software engineering practices• Design and implement ML engineering capabilities such as model serving, monitoring, evaluation, and retraining• Partner with data scientists to productionise models and experiments efficiently• Contribute directly to data preparation, feature engineering, experimentation, and modelling when required• Drive technical design reviews and provide mentorship to engineers and data scientists• Ensure AI solutions meet Mastercard standards for performance, reliability, security, and governance• Collaborate closely with platform, security, and infrastructure teams to ship responsibly at scale All about you • Strong experience as a hands-on AI engineer, ML engineer, or senior software engineer working on production AI systems• Solid foundations in software engineering, system design, and distributed systems• Proven experience productionising machine learning models and operating them at scale• Comfortable working across data engineering, ML engineering, and applied data science tasks• Experience with large-scale data platforms and modern ML/AI tooling• Strong problem-solving skills and ability to work with ambiguous requirements• Ability to influence technical direction without formal people management responsibility• Clear communication skills and comfort collaborating across functions What Makes You Stand Out• You have built and operated AI or agentic applications that run in real production environments• Hands-on experience implementing agent-based or LLM-powered systems beyond simple POCs• Strong intuition for reliability, observability, and failure handling in AI systems• Ability to move fluidly between engineering execution and applied modeling when needed• Track record of raising the technical bar for teams through code, design, and mentorship Corporate Security Responsibility Every person working for, or on behalf of, Mastercard is responsible for information security. All activities involving access to Mastercard assets, information, and networks come with an inherent risk to the organisation and therefore it is expected that the successful candidate must:• Abide by Mastercard's security policies and practices• Ensure the confidentiality and integrity of the information being accessed• Report any suspected information security violation or breach• Complete all mandatory security trainings in accordance with Mastercard's guidelines Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: - Abide by Mastercard's security policies and practices; - Ensure the confidentiality and integrity of the information being accessed; - Report any suspected information security violation or breach, and - Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We’re also a mission-driven company. We cultivate a culture that gives every CrowdStriker both the flexibility and autonomy to own their careers. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you. About the Role: This role sits at the intersection of AI application engineering and platform reliability within CrowdStrike’s Core Tech, Go To Market IT Apps Team — a team of Architects, Engineers, QA, BSAs, and Product Owners delivering highly Reliable, Scalable, and Secure Infrastructure and Automation Services across GTM Applications to accelerate Business Velocity and Operational Excellence. As a hybrid AI Engineer (Dev + DevOps), you will build and own the full lifecycle of agentic AI solutions: from designing LLM-powered workflows and autonomous agents to engineering the CI/CD pipelines, infrastructure-as-code, platform observability, and DevSecOps practices that make those solutions production-grade and enterprise-ready. As part of the GTM AI Pod, every member is expected to embrace Agentic AI technologies, operate with an open-source AI engineering mindset, and actively contribute to building the next generation of intelligent GTM workflows. You will not hand off your code to another team to deploy — you own it end to end. What You’ll Do: - Lead engineering delivery for agentic AI capabilities across GTM stakeholders and technology stacks (Salesforce, Slack, third-party apps, and in-house platforms), owning requirements through production deployment and post-release observability. - Design and build LLM-powered workflows, autonomous agents, and multi-agent systems using Agentcore, Slack, Model Context Protocols (MCPs), LangChain, and LangGraph — then ship them via automated pipelines you maintain. - Define scalable enterprise AI architecture patterns: model routing, orchestration, memory management, context-window governance, and multi-tenant isolation strategies. - Design and optimize RAG systems, semantic search pipelines, vector retrieval strategies, and enterprise knowledge-grounding frameworks for GTM data domains. - Build and maintain Salesforce Apex, Lightning Web Components, Platform Events, and Agentforce agent actions, integrating them with AI back-ends through secure, event-driven patterns. - Build and operate platform observability stacks (tracing, logging, alerting) and AI-specific metrics while managing infrastructure-as-code (Terraform / CDK) across AWS Bedrock and Vertex AI. - Implement DevSecOps and evaluation frameworks: supply-chain security, prompt benchmarking, hallucination reduction, and automated regression testing for non-deterministic outputs. - Define error handling, fallback strategies, and graceful degradation patterns for non-deterministic AI systems, including circuit-breaker patterns at both the application and infrastructure layers. - Retire legacy integrations and replace them with modern, agentic, event-driven architectures, eliminating manual toil through automation and self-healing runbooks. - Champion engineering excellence: code reviews, runbook documentation, blameless post-mortems, and capacity planning that spans both application logic and underlying compute. - Evaluate AI vendors and platforms with a strategic build-vs-buy mindset, factoring in total cost of ownership, compliance posture, and operational burden. - Identify, scope, and automate manual GTM processes to increase organizational leverage and reduce time-to-insight for go-to-market teams. What You’ll Need: - Bachelor’s degree in Computer Science, Engineering, or a related field. - 5+ years of software engineering experience, with meaningful exposure to both application development and platform/infrastructure responsibilities. - Strong proficiency in Python and TypeScript/JavaScript for AI application development, automation scripting, and infrastructure tooling. - Hands-on production experience with agentic AI frameworks, document parsing and structured extraction pipelines, autonomous agents, and LLM-powered systems at enterprise scale. - Solid working knowledge of modern AI orchestration frameworks: LangGraph, Semantic Kernel, CrewAI, AutoGen, MCP, and/or LangChain. - Demonstrable experience building and maintaining CI/CD pipelines (GitHub Actions, Jenkins, or Copado) and practicing GitOps or trunk-based delivery for both application and infrastructure code. - Proficiency with container and orchestration runtimes (Docker, Kubernetes or equivalent) and familiarity with service mesh, secrets management, and configuration management patterns. - Salesforce development experience: Apex, LWC, REST/SOAP integrations, Platform Events, and Agentforce agent actions. - Proficiency with vector databases (Pinecone, pgvector, Weaviate, or similar) and retrieval optimization techniques for RAG systems. - Solid understanding of DevSecOps practices: supply-chain security, SAST/DAST integration, secrets rotation, and least-privilege cloud IAM. Bonus Points: - Salesforce Platform Developer II, Application Architect, or DevOps Engineer certification. - Experience building Slack apps, Slack Workflow Builder, or Slack-integrated agentic workflows. - Hands-on experience with Salesforce Einstein / Agentforce platform development. - Demonstrated contributions to open-source AI or DevOps tooling (LangChain, LlamaIndex, Terraform providers, or similar). - Exposure to fine-tuning, RLHF, or model evaluation pipelines on domain-specific GTM datasets. - Experience designing or operating model routing platforms, enterprise AI control planes, or multi-model gateway patterns (e.g., LiteLLM, OpenRouter). - Background in platform engineering, SRE, or cloud infrastructure with a measured focus on SLOs, error budgets, and reliability engineering practices. - Familiarity with AI governance, responsible AI frameworks, or MLOps maturity models as they apply to enterprise GTM systems. #LI-DP1 #LI-Remote Benefits of Working at CrowdStrike: - Market leader in compensation and equity awards - Comprehensive physical and mental wellness programs - Competitive vacation and holidays for recharge - Paid parental and adoption leaves - Professional development opportunities for all employees regardless of level or role - Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections - Vibrant office culture with world class amenities - Great Place to Work Certified™ across the globe CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program. CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions--including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay-offs, return from lay-off, terminations and social/recreational programs--on valid job requirements. If you need assistance accessing or reviewing the information on this website or need help submitting an application for employment or requesting an accommodation, please contact us at recruiting@crowdstrike.com for further assistance.

Role Description As a Senior Full-Stack AI Engineer, you will play a critical hands-on role in building and evolving Superbench's AI-powered platform. Working closely with product and leadership, you will design, develop, and ship intelligent, customer-facing features that leverage modern AI capabilities. - Design and build AI-powered product features, including conversational interfaces, RAG pipelines, and multi-step / multi-agent workflows. - Own the implementation of backend and frontend systems across the Superbench platform. - Translate product requirements into scalable technical solutions, particularly for AI-driven use cases. - Work hands-on across the stack: Node.js/TypeScript and Python backend services, React frontend applications. - Integrate LLMs and AI tooling into production systems, ensuring reliability, performance, and strong user experience. - Build and maintain APIs, services, and data pipelines that support AI functionality. - Collaborate closely with product and design to iterate quickly on AI-driven features. - Contribute to engineering best practices around testing, code quality, and system reliability. - Participate in code reviews and support knowledge sharing across the team. Qualifications - 6+ years of professional software engineering experience, with a strong focus on building production systems. - 4+ years of backend engineering experience, primarily using Node.js frameworks (e.g. Express, NestJS) and modern TypeScript. - 2+ years of frontend engineering experience building user-facing applications with React. - 2+ years of practical experience building and integrating AI systems into production applications. - Deep understanding of JavaScript and TypeScript. - Strong experience designing and building scalable backend systems, APIs, and services. - Solid experience with relational databases (e.g. PostgreSQL, MySQL), including schema design and query optimization. - Hands-on experience with NoSQL databases (e.g. MongoDB). - Hands-on Python experience (2+ years), particularly for AI workflows, data processing, or backend services. - Strong experience building AI-powered customer-facing features, including: - Retrieval-Augmented Generation (RAG) pipelines. - Multi-step and/or multi-agent AI workflows. - Prompt design, evaluation, and iteration. - Tool-using agents and orchestration frameworks. - Experience working with AI frameworks and tools such as OpenAI SDK, LangGraph, MCP, or similar. - Hands-on experience with vector databases (e.g. Pinecone or equivalents). - Proven experience integrating complex AI flows into real user-facing products. - Strong problem-solving skills and ability to work in ambiguous environments. - Strong communication skills, with the ability to explain technical concepts clearly. - Strong spoken and written English. Requirements - Experience working in early-stage startups or fast-paced product environments (nice to have). - Familiarity with cloud platforms (e.g. GCP), CI/CD pipelines, and basic DevOps practices (nice to have). - Experience with event-driven architectures, background jobs, or message queues (nice to have). - Experience building real-time or conversational systems (e.g. chat, messaging, workflow automation) (nice to have). - Exposure to analytics, data pipelines, or reporting systems (nice to have). - Experience working with multi-tenant SaaS platforms (nice to have). - Familiarity with security best practices, authentication/authorization, and data privacy considerations (nice to have). - Experience collaborating in remote or distributed teams (nice to have). Benefits - Fully remote role with a distributed team. - Flexible working hours - we care about outcomes, not clock-watching. - Autonomy to structure your day, with clear communication and accountability. - A true leadership role in an early-stage startup. - Ownership over core technical decisions during a critical company pivot. - Direct influence on product direction, architecture, and long-term technical strategy. - Competitive compensation, commensurate with experience and seniority. - MacBook Pro provided. - Unlimited PTO (after a 3-month probationary period). - Grow into a long-term technical leader as the company scales. - Deepen your expertise in AI-first product development, including conversational AI, RAG, and agentic systems. - Work closely with founders and leadership. - Freedom to experiment, learn, and introduce better tools, processes, and practices.